PowerSearch MCP
Planned integration for exporting metrics to Prometheus for monitoring and observability of the MCP server.
Provides optional caching of search and fetch results using Redis storage backend to improve performance and reduce redundant requests.
Integrates with SearXNG meta search engine to perform web searches across multiple configurable engines with language, safe-search, and pagination options.
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., "@PowerSearch MCPsearch for recent climate change studies and summarize the top result"
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.
PowerSearch MCP
PowerSearch MCP helps AI agents search and retrieve content from the public web with fewer broken fetches and clean, AI-friendly outputs ready to cite.
TL;DR
Step 1: Clone the repository then run initialize the virtual environment:
git clone https://github.com/theobjectivedad/powersearch-mcp.gitStep 2: Initialize the virtual environment:
cd powersearch-mcp
make initStep 3: Activate the virtual environment:
source .venv/bin/activateStep 4: Create a .env file with your desired configuration, use example-configs/example.env as a starting point.
cp example-configs/example.env .envStep 5: (Optional) run a local instance of SearXNG:
docker run -d \
--name searxng-local \
--pull=always \
--restart unless-stopped \
-p 127.0.0.1:9876:8080 \
--tmpfs /etc/searxng:rw,noexec,nosuid,size=16m \
--tmpfs /tmp:rw,noexec,nosuid,size=512m \
--cap-drop=ALL \
--security-opt=no-new-privileges:true \
--health-cmd='python3 -c "import urllib.request; urllib.request.urlopen(\"http://127.0.0.1:8080/\", timeout=3).read(1)"' \
--health-interval=10s \
--health-timeout=3s \
--health-retries=10 \
--health-start-period=15s \
--env SEARXNG_SETTINGS_PATH=/settings.yml \
--volume "$(pwd)/searxng.yaml:/settings.yml:ro" \
searxng/searxngStep 6: Run PowerSearch via FastMCP:
fastmcp run \
src/powersearch_mcp/app.py \
--transport=streamable-http \
--skip-source \
--skip-envStep 7: Point your AI agent at http://localhost:8099/mcp to start searching the web!
Feature Roadmap
✅ SearXNG-backed meta search with configurable engines, language, safe-search, and pagination
✅ Strong anti-bot fetching implementation via Scrapling and Camoufox
✅ Search response caching at the tool-level to memory, disk, and Redis storage backends
✅ Automatic retries with exponential backoff for both search and fetch operations
✅ AI Agent-friendly responses: HTML pages are converted to markdown automatically via Trafilatura
✅ Support for STDIO and streaming HTTP transports
✅ Health check endpoint for HTTP transport
✅ Extensive configuration suitable for many deployment scenarios
✅ Authentication support for both JWT and opaque tokens
✅ Authorization support for embedded Eunomia policies
✅ Auto summarization of search results via MCP sampling
✅ Optional server-side fallback for clients that don't support MCP sampling
✅ Public Docker image on Docker Hub
🗓️ (Future) Client selectable synchronous (current behavior) or asynchronous SEP-1686 execution for search / fetch tools
🗓️ (Future) Prometheus metrics exporter
🗓️ (Future) Helm chart
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