searxng-mcp-bridge
Allows searching the web via a private SearXNG instance, returning results with title, URL, content, and engine.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@searxng-mcp-bridgesearch for latest AI news"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
searxng-mcp-bridge
A minimal MCP server that exposes a private
SearXNG instance as a search tool over
streamable-HTTP, so it can be used as a web-search tool from the
llama.cpp WebUI (or any MCP client that
speaks streamable-HTTP / SSE).
It is deliberately tiny — one file, two dependencies (fastmcp, httpx) — as an
auditable alternative to heavier SearXNG MCP packages.
Built for local networks or VPNs — not public internet exposure. This
bridge serves an unauthenticated search endpoint. Run it on a trusted LAN
or VPN only; do not bind it to a public interface, port-forward it, or place it
on an internet-facing host. The same applies to the SearXNG instance behind it
and to llama-server's experimental --ui-mcp-proxy.
Why this exists
There are existing SearXNG MCP servers, so why another one? Two reasons specific to this use case:
Transport. The llama.cpp WebUI is a browser-based MCP client, so it can only talk to MCP servers over a network transport (streamable-HTTP / SSE / WebSocket) — not stdio. Many published SearXNG MCP servers are stdio-first (aimed at Claude Desktop / IDEs), which doesn't fit here.
Footprint. This service runs unauthenticated on the local network, so its dependency and supply-chain surface matters. The most prominent PyPI option (
searxng-mcp) pulls in ~167 transitive packages — includinglitellm,llama-index-core,confluent-kafka, and a number of the author's own utility packages — for what is ultimately a thin wrapper around one HTTP endpoint. That's a lot of unrelated code to trust and keep updated.
Since the actual job is trivial (forward a query to SearXNG's JSON API and return the results), a single readable file with two well-known dependencies is easier to audit, deploy, and reason about than adopting a large general-purpose package.
Related MCP server: searxng-mcp
How it works
llama.cpp WebUI (browser MCP client)
│ streamable-HTTP http://<host>:8000/mcp
▼
server.py (this bridge)
│ GET /search?format=json
▼
SearXNG http://127.0.0.1:4000The WebUI's MCP client is browser-based and only supports network transports (streamable-HTTP / SSE / WebSocket) — not stdio — which is why this bridge serves HTTP.
Tool
search(query, max_results=10, categories=None, language=None, time_range=None)
— returns a list of {title, url, content, engine} from SearXNG.
Configuration (env vars)
Var | Default | Meaning |
|
| Base URL of the SearXNG instance |
|
| Bind address |
|
| Listen port |
|
| HTTP path for the MCP endpoint |
SearXNG must have the JSON format enabled (search.formats includes json in
settings.yml).
Install (systemd)
git clone <this-repo> /opt/searxng-mcp
cd /opt/searxng-mcp
./install.sh # creates .venv, installs the unit, enables + starts itinstall.sh rewrites the unit's paths/user to wherever the repo lives. Override
the interpreter or service user with PYTHON=, SERVICE_USER=, SERVICE_GROUP=.
Manage it:
sudo systemctl restart searxng-mcp
journalctl -u searxng-mcp -fRun manually (dev)
python3 -m venv .venv && .venv/bin/pip install -r requirements.txt
SEARXNG_URL=http://127.0.0.1:4000 .venv/bin/python server.pyWire into the llama.cpp WebUI
In WebUI → MCP Servers, add a server with transport Streamable HTTP and
URL http://<host>:8000/mcp. Use a tool-capable model served with --jinja.
Accessing the WebUI from another machine (CORS proxy)
If you open the llama.cpp WebUI from a different computer on your LAN/VPN
(i.e. not via localhost), the browser blocks the WebUI's direct connection to
the MCP server because it's a different origin (CORS). The fix is to route MCP
traffic through llama-server's built-in CORS proxy:
Start
llama-serverwith the proxy enabled (experimental — only on a trusted network; it lets the server make outbound requests on the client's behalf):llama-server ... --ui-mcp-proxy # (-ag / --agent also enables it, plus all built-in server tools)In the WebUI, add the MCP server as above and let it connect. The first attempt will fail from a remote browser — this is expected.
Open that server's settings and enable the "Use llama-server proxy" switch, then reconnect. (The switch is greyed out with a hint to pass
--ui-mcp-proxyif the server wasn't started with the flag, and it only becomes relevant once a direct connection has failed.)
When the WebUI is opened on the same machine via localhost, the proxy isn't
needed.
Tested clients
The bridge speaks standard MCP over streamable-HTTP, so it should work with any client that supports that transport. Confirmed working with:
llama.cpp WebUI — add it under MCP Servers as a Streamable HTTP server at
http://<host>:8000/mcp(see above).Page Assist (browser extension) — works well; add it as a streamable-HTTP MCP server pointing at the same URL.
Tested another client? PRs adding it to this list are welcome.
Screenshots
llama.cpp WebUI — the bridge added under MCP Servers with the Use llama-server proxy switch enabled (see the CORS-proxy note above):

Page Assist — the bridge registered as an HTTP MCP server:

Security note
This is designed for local networks or VPNs, not public internet exposure.
The bridge has no authentication — anyone who can reach its port can run
searches through your SearXNG instance. Binding HOST=0.0.0.0 (the default)
exposes it on every reachable network interface, including your LAN and VPN.
Keep it on a trusted network. Do not put it on a public/internet-facing host, port-forward it, or expose it through a reverse proxy without your own authentication in front.
Use
HOST=127.0.0.1if you only need local (same-machine) access.Otherwise restrict access at the firewall to the specific hosts that need it.
llama-server's--ui-mcp-proxyis experimental and similarly assumes a trusted network — enable it only there.
License
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- Alicense-qualityDmaintenanceAn MCP server that wraps a local SearXNG instance to provide private, customizable web search capabilities. It enables AI assistants to perform queries with support for specific parameters like results limits, language, and time ranges.Last updated248MIT
- FlicenseAqualityAmaintenanceAn MCP server for SearXNG that provides web search capabilities with concise model-visible output while preserving full result payloads in metadata. It supports search, parallel fetching, URL extraction, and research workflows through both local stdio and streamable HTTP transports.Last updated7
- Alicense-qualityDmaintenanceA minimal, production-ready MCP server enabling LLMs to perform web searches via DuckDuckGo without API keys, supporting SSE streaming and LM Studio compatibility.Last updated1BSD 3-Clause
- AlicenseAqualityAmaintenanceMCP server for private web search via self-hosted SearXNG with local reranking, full-page content fetching via Firecrawl, and optional Ollama-powered query expansion and summaries.Last updated729316MIT
Related MCP Connectors
Serper MCP — wraps the Serper Google Search API (serper.dev)
MCP server for Google search results via SERP API
Local-first RAG engine with MCP server for AI agent integration.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/designcomputer/searxng-mcp-bridge'
If you have feedback or need assistance with the MCP directory API, please join our Discord server