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Searxng Mcp

CLI or API | MCP

Documentation — Installation, deployment, usage across the MCP tool, Python API, and console scripts, and guidance for provisioning the SearXNG instance are maintained in the official documentation.

Overview

Searxng Mcp is a production-grade Agent and Model Context Protocol (MCP) server designed to interface directly with SearXNG Search Engine MCP Server for Agentic AI!.

Key Features

• Consolidated Action-Routed MCP Tools: Minimizes token overhead and eliminates tool bloat in LLM contexts by grouping methods into optimized, togglable tool modules.
• Enterprise-Grade Security: Complete support for Eunomia policies, OIDC token delegation, and granular execution context tracking.
• Native Telemetry & Tracing: Out-of-the-box OpenTelemetry exports and native Langfuse tracing.

CLI or API

This agent wraps the SearXNG Search Engine MCP Server for Agentic AI! API. The operator can interact with it programmatically or via its integrated execution entrypoints.

Detailed instructions on how to use the underlying API wrappers, extended schema bindings, and developer SDK references are maintained in docs/index.md.

MCP

This server use dynamic Action-Routed tools to optimize token overhead and maximize IDE compatibility.

Available MCP Tools

The table below is auto-generated from the MCP server — do not edit by hand.

Condensed action-routed tools (MCP_TOOL_MODE=condensed)

4 action-routed tool(s) · 0 verbose 1:1 tool(s). Each is enabled unless its <DOMAIN>TOOL toggle is set false; MCP_TOOL_MODE selects the surface (intent default — the six verb-tools, granular set loaded on demand · condensed action-routed · verbose 1:1 · both). Auto-generated — do not edit.

Detailed tool schemas, parameter shapes, and validation constraints are preserved in docs/usage.md.

Dynamic Tool Selection & Visibility

This MCP server supports dynamic toolset selection and visibility filtering at runtime. This allows the operator to restrict the set of exposed tools to prevent blowing up the LLM's context window.

The operator can configure tool filtering via multiple input channels:

• CLI Arguments: Pass --tools or --toolsets (or their disabled counterparts --disabled-tools and --disabled-toolsets) during startup.
• Environment Variables: Define standard environment variables:
  • MCP_ENABLED_TOOLS / MCP_DISABLED_TOOLS
  • MCP_ENABLED_TAGS / MCP_DISABLED_TAGS
• HTTP SSE Request Headers: Pass custom headers during transport initialization:
  • x-mcp-enabled-tools / x-mcp-disabled-tools
  • x-mcp-enabled-tags / x-mcp-disabled-tags
• HTTP SSE Request Query Parameters: Append query parameters directly to the operator's transport connection URL:
  • ?tools=tool1,tool2
  • ?tags=tag1

When query strings or parameters are supplied, an LLM-free Knowledge Graph resolution layer (using DynamicToolOrchestrator) matches query intents against known tool tags, names, or descriptions, with safe fallback and automated 24-hour background cache refreshing.

MCP Configuration Examples

Install the connector-focused [mcp] extra. Examples use searxng-mcp[mcp] to add FastMCP / FastAPI through agent-connector-sdk; the required Agent Connector SDK core still carries epistemic-graph[full]. The [agent-runtime] extra additionally enables model orchestration.

stdio Transport (local IDEs — Cursor, Claude Desktop, VS Code)

{
  "mcpServers": {
    "searxng-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "searxng-mcp[mcp]",
        "searxng-mcp"
      ],
      "env": {
        "MCP_TOOL_MODE": "intent",
        "SEARCH_APPTOOL": "true",
        "SEARXNG_EMBEDDED": "true",
        "USE_RANDOM_INSTANCE": "false"
      }
    }
  }
}

Runtime references require an alias-aware launcher such as Arbora. Other launchers must omit those entries and inject the resolved values through their own runtime secret boundary.

Streamable-HTTP Transport (networked / production)

{
  "mcpServers": {
    "searxng-mcp": {
      "command": "uvx",
      "args": [
        "--from",
        "searxng-mcp[mcp]",
        "searxng-mcp",
        "--transport",
        "streamable-http",
        "--port",
        "8000"
      ],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "127.0.0.1",
        "PORT": "8000",
        "MCP_TOOL_MODE": "intent",
        "SEARCH_APPTOOL": "true",
        "SEARXNG_EMBEDDED": "true",
        "USE_RANDOM_INSTANCE": "false"
      }
    }
  }
}

Alternatively, connect to a pre-deployed Streamable-HTTP instance by url:

{
  "mcpServers": {
    "searxng-mcp": {
      "url": "http://localhost:8000/searxng-mcp/mcp"
    }
  }
}

Run a reviewed container image as a least-privilege stdio child (no listener or published port):

docker run -i --rm \
  --read-only \
  --cap-drop=ALL \
  --security-opt=no-new-privileges \
  --pids-limit=256 \
  --tmpfs /tmp:rw,noexec,nosuid,nodev,size=64m \
  -e TRANSPORT=stdio \
  -e MCP_TOOL_MODE=intent \
  -e SEARCH_APPTOOL=true \
  -e SEARXNG_EMBEDDED=true \
  -e USE_RANDOM_INSTANCE=false \
  registry.example.invalid/searxng-mcp@sha256:<digest> searxng-mcp

For containerized network HTTP, supply an authenticated TLS ingress (or direct server TLS), exact MCP_ALLOWED_HOSTS, and an exact trusted-proxy CIDR policy through the operator-owned deployment profile. The generator does not emit an unauthenticated non-loopback listener.

Auto-generated from the code-read env surface (MCP_TOOL_MODE + package vars) — do not edit.

Additional Deployment Options

searxng-mcp can run as a local stdio process or container, or behind a remote network boundary. The Deployment guide carries the detailed transport contract.

• Local container — launch a reviewed immutable image as a least-privilege stdio child with no listener or published port.
• Remote URL — connect through an operator-supplied authenticated HTTPS ingress. Keep its URL, outbound identity references, trust profile, and exact MCP_ALLOWED_HOSTS in AgentConfig.

Agent

Set credentials

export SEARXNG_URL="your_value"

Connector-focused MCP server (includes the shared graph engine)

uv pip install "searxng-mcp[mcp]"

Everything (development)

uv pip install "searxng-mcp[all]" # or: python -m pip install "searxng-mcp[all]"

### Container images (`:mcp`)

One multi-stage `docker/Dockerfile` builds the MCP-only image (`--target mcp`):

| Image tag | Build target | Contents | Entrypoint |
|-----------|--------------|----------|------------|
| `example/searxng-mcp:mcp` | `--target mcp` | `searxng-mcp[mcp]` — **connector-focused**, includes `epistemic-graph[full]`; no model-orchestration stack | `searxng-mcp` |

```bash
docker build --target mcp   -t example/searxng-mcp:mcp    docker/   # connector-focused MCP server