MetaSearchMCP

Open-source metasearch backend for MCP, AI agents, and LLM workflows.

MetaSearchMCP aggregates results from multiple search providers, normalizes them into a stable JSON schema, and exposes both an HTTP API and an MCP server for agent tooling.

Positioning

• MCP-first metasearch backend
• Structured search API for AI pipelines
• Multi-provider search orchestration with deduplication and fallback
• Python FastAPI alternative to browser-first metasearch projects

Why It Exists

Most search aggregators are designed around browser UX: HTML pages, pagination, and interactive result cards. Agents and LLM workflows need a different contract: predictable JSON, stable field names, partial-failure tolerance, and provider-level execution metadata.

MetaSearchMCP is built for that machine-consumable workflow. It is not a SearXNG clone. The design is centered on search orchestration, normalized contracts, and MCP integration.

Core Features

• Concurrent multi-provider aggregation
• Unified result schema for web, academic, developer, and knowledge sources
• Provider-level timeout isolation and partial-failure handling
• Result deduplication across engines
• Provider selection by explicit names or semantic tags such as web, academic, code, and google
• Final result caps for agent-friendly payload sizing
• HTTP API with OpenAPI docs
• MCP server over stdio for Claude Desktop, Cline, Continue, and similar clients
• Configurable provider allowlist via environment variables

Google Support

Google is intentionally not scraped directly in this project.

In practice, Google's anti-bot and risk-control systems make self-hosted scraping brittle and expensive to maintain. For a backend intended for reliable MCP and AI workloads, hosted Google providers are the more practical option.

Currently supported Google providers:

Both are low-cost options. For smaller or occasional workloads, serpbase.dev is usually the lower-cost choice.

Supported Providers

Google

Web Search

Knowledge And Reference

Developer Sources

Academic Sources

Finance Sources

Installation

One-command local install:

python scripts/install.py

Install, run tests, and start the HTTP API:

python scripts/install.py --dev --test --run

Deploy with Docker Compose:

python scripts/install.py --mode docker

The installer creates .env from .env.example when .env does not already exist. Existing .env files are kept unless --force-env is passed.

Manual install:

git clone https://github.com/gefsikatsinelou/MetaSearchMCP
cd MetaSearchMCP
pip install -e ".[dev]"

Or with uv:

uv pip install -e ".[dev]"

Configuration

Copy .env.example to .env and configure any providers you want to enable.

cp .env.example .env

Key settings:

HOST=0.0.0.0
PORT=8000
DEFAULT_TIMEOUT=10
AGGREGATOR_TIMEOUT=15

SERPBASE_API_KEY=
SERPER_API_KEY=
BRAVE_API_KEY=
GITHUB_TOKEN=
STACKEXCHANGE_API_KEY=
REDDIT_CLIENT_ID=
REDDIT_CLIENT_SECRET=
NCBI_API_KEY=
SEMANTIC_SCHOLAR_API_KEY=
ALPHA_VANTAGE_API_KEY=
FINNHUB_API_KEY=

ENABLED_PROVIDERS=
ALLOW_UNSTABLE_PROVIDERS=false
MAX_RESULTS_PER_PROVIDER=10

Running

HTTP API

python -m metasearchmcp.server
# or
metasearchmcp

The API starts on http://localhost:8000.

MCP Server

python -m metasearchmcp.broker
# or
metasearchmcp-mcp

The MCP server communicates over stdio.

Docker

docker build -t metasearchmcp .
docker run --rm -p 8000:8000 --env-file .env metasearchmcp

Or with Compose:

docker compose up --build

HTTP API

POST /search

Aggregate across all enabled providers or a selected provider subset.

curl -X POST http://localhost:8000/search \
  -H "Content-Type: application/json" \
  -d '{
    "query": "rust async runtime",
    "providers": ["duckduckgo", "wikipedia"],
    "params": {"num_results": 5, "max_total_results": 8, "language": "en"}
  }'

You can also narrow providers by tags:

curl -X POST http://localhost:8000/search \
  -H "Content-Type: application/json" \
  -d '{
    "query": "transformer attention",
    "tags": ["academic", "knowledge"],
    "params": {"num_results": 5, "max_total_results": 6}
  }'

num_results controls how many results each provider can contribute. max_total_results caps the final merged response after deduplication.

POST /search/google

Search Google through a configured hosted provider.

curl -X POST http://localhost:8000/search/google \
  -H "Content-Type: application/json" \
  -d '{"query": "site:github.com rust tokio"}'

GET /providers

Return the currently available provider catalog.

The response includes provider descriptions and a tag-to-provider index for quick discovery.

You can filter the catalog by tag:

curl "http://localhost:8000/providers?tag=academic&tag=web"

GET /health

Simple health check endpoint. Returns service status, version, provider count, and the current provider name list.

Response Schema

Every aggregated response includes:

• engine
• query
• results
• related_searches
• suggestions
• answer_box
• timing_ms
• providers
• errors

Every result item includes:

• title
• url
• snippet
• source
• rank
• provider
• published_date
• extra

Example response:

{
  "engine": "metasearchmcp",
  "query": "rust async runtime",
  "results": [
    {
      "title": "Tokio - An asynchronous Rust runtime",
      "url": "https://tokio.rs",
      "snippet": "Tokio is an event-driven, non-blocking I/O platform...",
      "source": "tokio.rs",
      "rank": 1,
      "provider": "duckduckgo",
      "published_date": null,
      "extra": {}
    }
  ],
  "related_searches": [],
  "suggestions": [],
  "answer_box": null,
  "timing_ms": 843.2,
  "providers": [
    {
      "name": "duckduckgo",
      "success": true,
      "result_count": 10,
      "latency_ms": 840.1,
      "error": null
    }
  ],
  "errors": []
}

MCP Tools

MetaSearchMCP exposes these MCP tools:

• search_web
• search_google
• search_academic
• search_github
• compare_engines

search_web also accepts optional tags so agents can limit search to categories such as web, academic, code, or google. All search tools accept max_total_results to keep the final payload compact.

Example Claude Desktop config:

{
  "mcpServers": {
    "MetaSearchMCP": {
      "command": "metasearchmcp-mcp",
      "env": {
        "SERPBASE_API_KEY": "your_key",
        "SERPER_API_KEY": "your_key"
      }
    }
  }
}

Development

pip install -e ".[dev]"
pytest
uvicorn metasearchmcp.server:app --reload

Architecture

The public package is organized around these modules:

• contracts.py: request and response models
• catalog.py: provider discovery and selection
• orchestrator.py: concurrent search execution and response assembly
• merge.py: URL normalization and deduplication
• server.py: FastAPI entrypoint
• broker.py: MCP entrypoint

Legacy module names are kept as compatibility shims for earlier imports.

Roadmap

• Caching and provider-aware query reuse
• Better scoring and ranking signals across providers
• Streaming aggregation responses
• Provider health telemetry
• More first-party API integrations where they improve reliability

License

MIT