# Docfork MCP Server (`agentify/docfork-mcp-server`) Actor Access @latest documentation and code examples from 9000+ libraries in a single tool call - **URL**: https://apify.com/agentify/docfork-mcp-server.md - **Developed by:** [agentify](https://apify.com/agentify) (community) - **Categories:** AI, MCP servers, Open source - **Stats:** 10 total users, 1 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 ## Docfork MCP Server [![Apify Actor Badge](https://apify.com/actor-badge?actor=mcp-servers/docfork-mcp-server)](https://apify.com/actor/mcp-servers/docfork-mcp-server) ๐ŸŒฟ Access @latest documentation and code examples from 9000+ libraries in a single tool call. **About this MCP Server:** To understand how to connect to and utilize this MCP server, please refer to the official Model Context Protocol documentation at [mcp.apify.com](https://mcp.apify.com). ### Connection URL MCP clients can connect to this server at: ```text https://mcp-servers--docfork-mcp-server.apify.actor/mcp ```` ### Client Configuration To connect to this MCP server, use the following configuration in your MCP client: ```json { "mcpServers": { "docfork": { "url": "https://mcp-servers--docfork-mcp-server.apify.actor/mcp", "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" } } } } ``` **Note:** Replace `YOUR_APIFY_TOKEN` with your actual Apify API token. You can find your token in the [Apify Console](https://console.apify.com/account/integrations). ### Links - **GitHub Repository**: https://github.com/docfork/docfork-mcp - **Actor Repository**: https://github.com/apify/mcp-servers - **Apify MCP Documentation**: https://mcp.apify.com ### ๐Ÿšฉ Claim this MCP server All credits to the original authors of https://github.com/docfork/docfork-mcp To claim this server, please write to . *** ### โŒ The Problem: Expired Knowledge - Out of date code examples & stale data from year-old model training - Hallucinated syntax & APIs - Old or mismatched versions ### โœ… The Solution: @latest docs at warp speed - Always in sync with the latest version of docs - Accurate descriptions and code examples - Sub-second retrieval results (500ms @ p95) in your AI code editor Docfork MCP pulls @latest documentation and code examples straight from the source - and adds them right into your context. Just tell Cursor to **`use docfork`**: ```txt Create a basic Next.js app with the App Router. use docfork ``` ### ๐Ÿ› ๏ธ Available Tools Docfork MCP provides the following tool that LLMs can use: - `get-library-docs`: Searches the library and returns its documentation. - `libraryName` (required): The name of the library to search for - `topic` (required): Focus the docs on a specific topic (e.g., "routing", "hooks") - `tokens` (optional, default 10000, max 50000): Max number of tokens to return. Values less than the configured `DEFAULT_MINIMUM_TOKENS` value or the default value of 10000 are automatically increased to that value. ### ๐Ÿ’ก Tips #### Add a Rule If you don't want to add `use docfork` to every prompt, you can define a simple rule from your `Cursor Settings > Rules` section in Cursor (or the equivalent in your MCP client) to auto-invoke Docfork on any code question: ```markdown --- alwaysApply: true --- when the user requests code examples, setup or configuration steps, or library/API documentation use docfork. ``` From then on you'll get Docfork's docs in any related conversation without typing anything extra. You can add your use cases to the match part. #### Use Specific Library Names When you know exactly which library you want to use, be specific in your prompts. This helps Docfork find the right documentation faster and more accurately: ```txt implement basic authentication with supabase. use docfork ``` ```txt create a Next.js middleware for rate limiting. use docfork ``` ```txt configure Tailwind CSS with custom typography. use docfork ``` The more specific you are about the library and what you want to accomplish, the better documentation you'll receive. ### โš ๏ธ Disclaimer Docfork is an open, community-driven catalogue. Although we review submissions, we make no warrantiesโ€”express or impliedโ€”about the accuracy, completeness, or security of any linked documentation or code. Projects listed here are created and maintained by their respective authors, not by Docfork. If you spot content that is suspicious, inappropriate, or potentially harmful, please contact us. By using Docfork, you agree to do so at your own discretion and risk. ### ๐ŸŒŸ Let's Connect! Stay in the loop and meet the community: - ๐Ÿฆ Follow us on [X](https://x.com/docfork_ai) for product news and updates - ๐ŸŒ Visit our [Website](https://docfork.com) ### References 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) - [Apify MCP Server](https://docs.apify.com/platform/integrations/mcp) - [Webinar: Building and Monetizing MCP Servers on Apify](https://www.youtube.com/watch?v=w3AH3jIrXXo) - [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU) # Actor input Schema ## 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("agentify/docfork-mcp-server").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("agentify/docfork-mcp-server").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call agentify/docfork-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agentify/docfork-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Docfork MCP Server", "description": "Access @latest documentation and code examples from 9000+ libraries in a single tool call", "version": "0.0", "x-build-id": "zxOhsxYyjXUNGaUdV" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agentify~docfork-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agentify-docfork-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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~docfork-mcp-server/runs": { "post": { "operationId": "runs-sync-agentify-docfork-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~docfork-mcp-server/run-sync": { "post": { "operationId": "run-sync-agentify-docfork-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 } } } } } } } } } } ```