# Wikipedia MCP Server (`agentify/wikipedia-mcp-server`) Actor

MCP server for Wikipedia, providing LLMs and clients with real-time access to Wikipedia articles, summaries, sections, and related information via Apify Actor.

- **URL**: https://apify.com/agentify/wikipedia-mcp-server.md
- **Developed by:** [agentify](https://apify.com/agentify) (community)
- **Categories:** AI, MCP servers, Open source
- **Stats:** 23 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

## Wikipedia MCP Server (Apify Actor)

Model Context Protocol (MCP) server for Wikipedia, packaged as an [Apify Actor](https://apify.com/). Provides LLMs with real-time access to Wikipedia information.

### 🏃‍♂️ Quickstart (Local)

```sh
## Install dependencies
pip install -r requirements.txt

## Run the Actor (starts the MCP server via stdio)
python src/main.py
````

### 🛠️ Apify Actor Usage

This Actor launches the Wikipedia MCP server using stdio transport, suitable for Claude Desktop and other MCP clients.

#### Client connection example

```json
{
    "mcpServers": {
        "wikipedia": {
            "type": "stdio",
            "command": "python",
            "args": ["src/main.py"]
        }
    }
}
```

#### Environment variables

- `WIKIPEDIA_LANGUAGE` (optional): Set the Wikipedia language (e.g., `en`, `ja`).

### 💸 Pay-Per-Event (PPE) Mapping

See `.actor/pay_per_event.json` for tool pricing. Example (extremely cheap):

```json
{
    "actor-start": { "eventPriceUsd": 0.00001 },
    "search_wikipedia": { "eventPriceUsd": 0.00001 },
    "get_article": { "eventPriceUsd": 0.00001 },
    "get_summary": { "eventPriceUsd": 0.00001 },
    "get_sections": { "eventPriceUsd": 0.00001 },
    "get_links": { "eventPriceUsd": 0.00001 },
    "get_related_topics": { "eventPriceUsd": 0.00001 },
    "summarize_article_for_query": { "eventPriceUsd": 0.00001 },
    "summarize_article_section": { "eventPriceUsd": 0.00001 },
    "extract_key_facts": { "eventPriceUsd": 0.00001 }
}
```

### 📝 Features

- Search Wikipedia articles
- Retrieve article content, summaries, sections, links, related topics
- Multi-language support

### 🔗 Resources

- [MCP Protocol docs](https://mcp.apify.com)
- [Wikipedia MCP server upstream](https://github.com/rudra-ravi/wikipedia-mcp)
- [Apify MCP servers](https://github.com/apify/mcp-servers)

### 🏷️ Credits

- Wikipedia MCP server by [rudra-ravi](https://github.com/rudra-ravi/wikipedia-mcp)
- Apify Actorization by [Apify](https://apify.com/)

### 🧪 Testing

```sh
python src/main.py
## Or run via Apify CLI:
apify run
```

### 🛡️ Security

See [MseeP.ai Security Assessment Badge](https://mseep.net/pr/rudra-ravi-wikipedia-mcp-badge.png)

The template supports multiple charging approaches that you can customize based on your needs:

##### 1. Generic MCP charging

Charge for standard MCP operations with flat rates:

```json
{
    "actor-start": {
        "eventTitle": "MCP server startup",
        "eventDescription": "Initial fee for starting the Actor MCP Server",
        "eventPriceUsd": 0.1
    },
    "tool-call": {
        "eventTitle": "MCP tool call",
        "eventDescription": "Fee for executing MCP tools",
        "eventPriceUsd": 0.05
    },
    "resource-read": {
        "eventTitle": "MCP resource access",
        "eventDescription": "Fee for accessing full content or resources",
        "eventPriceUsd": 0.0001
    },
    "prompt-get": {
        "eventTitle": "MCP prompt processing",
        "eventDescription": "Fee for processing AI prompts",
        "eventPriceUsd": 0.0001
    }
}
```

##### 2. Domain-specific charging (arXiv example)

Charge different amounts for different tools based on computational cost:

```json
{
    "actor-start": {
        "eventTitle": "arXiv MCP server startup",
        "eventDescription": "Initial fee for starting the arXiv MCP Server Actor",
        "eventPriceUsd": 0.1
    },
    "search_papers": {
        "eventTitle": "arXiv paper search",
        "eventDescription": "Fee for searching papers on arXiv",
        "eventPriceUsd": 0.001
    },
    "list_papers": {
        "eventTitle": "arXiv paper listing",
        "eventDescription": "Fee for listing available papers",
        "eventPriceUsd": 0.001
    },
    "download_paper": {
        "eventTitle": "arXiv paper download",
        "eventDescription": "Fee for downloading a paper from arXiv",
        "eventPriceUsd": 0.001
    },
    "read_paper": {
        "eventTitle": "arXiv paper reading",
        "eventDescription": "Fee for reading the full content of a paper",
        "eventPriceUsd": 0.01
    }
}
```

##### 3. No charging (free service)

Comment out all charging lines in the code for a free service.

#### How to implement charging

1. **Define your events** in `.actor/pay_per_event.json` (see examples above). This file is not actually used at Apify platform but serves as a reference.

2. **Enable charging in code** by uncommenting the appropriate lines in `src/mcp_gateway.py`:

   ```python
   # For generic charging:
   await charge_mcp_operation(actor_charge_function, ChargeEvents.TOOL_CALL)

   # For domain-specific charging:
   if tool_name == 'search_papers':
       await charge_mcp_operation(actor_charge_function, ChargeEvents.SEARCH_PAPERS)
   ```

3. **Add custom events** to `src/const.py` if needed:

   ```python
   class ChargeEvents(str, Enum):
       # Your custom events
       CUSTOM_OPERATION = 'custom-operation'
   ```

4. **Set up PPE model** on Apify:
   - Go to your Actor's **Publication settings**
   - Set the **Pricing model** to `Pay per event`
   - Add your pricing schema from `pay_per_event.json`

#### Authorized tools

This template includes **tool authorization** - only tools listed in `src/const.py` can be executed:

**Note**: The `TOOL_WHITELIST` dictionary only applies to **tools** (executable functions).
Prompts (like `deep-paper-analysis`) are handled separately and don't need to be added to this list.

Tool whitelist for MCP server
Only tools listed here will be present to the user and allowed to execute.
Format of the dictionary: {tool\_name: (charge\_event\_name, default\_count)}
To add new authorized tools, add an entry with the tool name and its charging configuration.

```python
TOOL_WHITELIST = {
    ChargeEvents.SEARCH_PAPERS.value: (ChargeEvents.SEARCH_PAPERS.value, 1),
    ChargeEvents.LIST_PAPERS.value: (ChargeEvents.LIST_PAPERS.value, 1),
    ChargeEvents.DOWNLOAD_PAPER.value: (ChargeEvents.DOWNLOAD_PAPER.value, 1),
    ChargeEvents.READ_PAPER.value: (ChargeEvents.READ_PAPER.value, 1),
}
```

**To add new tools:**

1. Add charge event to `ChargeEvents` enum
2. Add tool entry to `TOOL_WHITELIST` dictionary with format: `tool_name: (event_name, count)`
3. Update pricing in `pay_per_event.json`
4. Update pricing at Apify platform

Unauthorized tools are blocked with clear error messages.

### 🔧 How it works

This template implements a MCP gateway that can connect to a stdio-based, Streamable HTTP, or SSE-based MCP server and expose it via [Streamable HTTP transport](https://modelcontextprotocol.io/specification/2025-06-18/basic/transports#streamable-http). Here's how it works:

#### Server types

1. **Stdio server** (`StdioServerParameters`):
   - Spawns a local process that implements the MCP protocol over stdio.
   - Configure using the `command` parameter to specify the executable and the `args` parameter for additional arguments.
   - Optionally, use the `env` parameter to pass environment variables to the process.

Example:

```python
server_type = ServerType.STDIO
MCP_SERVER_PARAMS = StdioServerParameters(
    command='uv',
    args=['run', 'arxiv-mcp-server'],
    env={'YOUR_ENV_VAR': os.getenv('YOUR-ENV-VAR')},  # Optional environment variables
)
```

2. **Remote server** (`RemoteServerParameters`):
   - Connects to a remote MCP server via HTTP or SSE transport.
   - Configure using the `url` parameter to specify the server's endpoint.
   - Set the appropriate `server_type` (ServerType.HTTP or ServerType.SSE).
   - Optionally, use the `headers` parameter to include custom headers (e.g., for authentication) and the `auth` parameter for additional authentication mechanisms.

Example:

```python
server_type = ServerType.HTTP
MCP_SERVER_PARAMS = RemoteServerParameters(
    url='https://mcp.apify.com',
    headers={'Authorization': 'Bearer YOUR-API-KEY'},  # Replace with your authentication token
)
```

Note: SSE transport is also supported by setting `server_type = ServerType.SSE`.

- **Tips**:
  - Ensure the remote server supports the transport type you're using and is accessible from the Actor's environment.
  - Use environment variables to securely store sensitive information like tokens or API keys.

##### Environment variables:

Environment variables can be securely stored and managed at the Actor level on the [Apify platform](https://docs.apify.com/platform/actors/development/programming-interface/environment-variables#custom-environment-variables). These variables are automatically injected into the Actor's runtime environment, allowing you to:

- Keep sensitive information like API keys secure.
- Simplify configuration by avoiding hardcoded values in your code.

#### Gateway implementation

The MCP gateway (`create_gateway` function) handles:

- Creating a Starlette web server with Streamable HTTP (`/mcp`) endpoint
- Managing connections to the underlying MCP server
- Forwarding requests and responses between clients and the MCP server
- Handling charging through the `actor_charge_function` (`Actor.charge` in Apify Actors)
- Tool authorization: Only allowing whitelisted tools to execute
- Access control: Blocking unauthorized tool calls with clear error messages

Key components:

- `create_gateway`: Creates an MCP server instance that acts as a gateway
- `charge_mcp_operation`: Handles charging for different MCP operations
- `TOOL_WHITELIST`: Dictionary mapping tool names to (event\_name, count) tuples for authorization and charging

#### MCP operations

The MCP gateway supports all standard MCP operations:

- `list_tools()`: List available tools
- `call_tool()`: Execute a tool with arguments
- `list_prompts()`: List available prompts
- `get_prompt()`: Get a specific prompt
- `list_resources()`: List available resources
- `read_resource()`: Read a specific resource

Each operation can be configured for charging in the PPE model.

### 📚 Resources

- [What is Anthropic's Model Context Protocol?](https://blog.apify.com/what-is-model-context-protocol/)
- [How to use MCP with Apify Actors](https://blog.apify.com/how-to-use-mcp/)
- [Apify MCP server](https://mcp.apify.com)
- [Apify MCP server documentation](https://docs.apify.com/platform/integrations/mcp)
- [Apify MCP client](https://apify.com/jiri.spilka/tester-mcp-client)
- [MCP Servers hosted at Apify](https://apify.com/store/categories/mcp-servers)
- [Model Context Protocol documentation](https://modelcontextprotocol.io)
- [Apify SDK documentation](https://docs.apify.com/sdk/js/)

### Getting started

For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-locally). To run the Actor use the following command:

```bash
apify run
```

### Deploy to Apify

#### Connect Git repository to Apify

If you've created a Git repository for the project, you can easily connect to Apify:

1. Go to [Actor creation page](https://console.apify.com/actors/new)
2. Click on **Link Git Repository** button

#### Push project on your local machine to Apify

You can also deploy the project on your local machine to Apify without the need for the Git repository.

1. Log in to Apify. You will need to provide your [Apify API Token](https://console.apify.com/account/integrations) to complete this action.

   ```bash
   apify login
   ```

2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under [Actors -> My Actors](https://console.apify.com/actors?tab=my).

   ```bash
   apify push
   ```

### Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

- [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js)
- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("agentify/wikipedia-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("agentify/wikipedia-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call agentify/wikipedia-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=agentify/wikipedia-mcp-server",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Wikipedia MCP Server",
        "description": "MCP server for Wikipedia, providing LLMs and clients with real-time access to Wikipedia articles, summaries, sections, and related information via Apify Actor.",
        "version": "0.0",
        "x-build-id": "0GuV4CyzdRcmDGynQ"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/agentify~wikipedia-mcp-server/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-agentify-wikipedia-mcp-server",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/agentify~wikipedia-mcp-server/runs": {
            "post": {
                "operationId": "runs-sync-agentify-wikipedia-mcp-server",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/agentify~wikipedia-mcp-server/run-sync": {
            "post": {
                "operationId": "run-sync-agentify-wikipedia-mcp-server",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "properties": {}
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```