SerpApi MCP Server
Retrieves parsed search results from Baidu search engine via SerpApi
Performs searches on DuckDuckGo and retrieves parsed search results via SerpApi
Retrieves parsed search results from eBay marketplace via SerpApi
Manages environment variables for the MCP server, specifically for storing and accessing the SerpApi API key
Performs searches on Google and retrieves parsed search results pages via SerpApi
Retrieves parsed search results from Walmart online store via SerpApi
Performs searches on YouTube and retrieves parsed video search results via SerpApi
Click on "Deploy 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., "@SerpApi MCP Serversearch for best coffee shops in Seattle with outdoor seating"
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.
SerpApi MCP Server
A Model Context Protocol (MCP) server implementation that integrates with SerpApi for comprehensive search engine results and data extraction.
Features
Multi-Engine Search: Google, Bing, Yahoo, DuckDuckGo, YouTube, eBay, and more
Engine Resources: Per-engine parameter schemas available via MCP resources (see Search Tool)
Real-time Weather Data: Location-based weather with forecasts via search queries
Stock Market Data: Company financials and market data through search integration
Dynamic Result Processing: Automatically detects and formats different result types
Flexible Response Modes: Complete or compact JSON responses
JSON Responses (default): Structured JSON output with complete or compact modes
Markdown Responses: Cut token usage by 50% on average and by more than 90% for APIs with complex nested JSON.
Interactive UI (MCP Apps): Opt-in
search_tableandsearch_dashboardtools that render results as an interactive UI in supporting hostsClaude Desktop Extension: One-click local install from an MCP Bundle (
.mcpb), see below
Related MCP server: SearXNG MCP Server
Quick Start
SerpApi MCP Server is available as a hosted service at mcp.serpapi.com. In order to connect to it, you need to provide an API key. You can find your API key on your SerpApi dashboard.
You can configure Claude Desktop to use the hosted server:
{
"mcpServers": {
"serpapi": {
"type": "http",
"url": "https://mcp.serpapi.com/YOUR_SERPAPI_API_KEY/mcp"
}
}
}You can also add the hosted server to these MCP clients:
OpenClaw
openclaw mcp add serpapi --url https://mcp.serpapi.com/YOUR_SERPAPI_API_KEY/mcp --transport streamable-httpClaude Code
claude mcp add --transport http serpapi https://mcp.serpapi.com/YOUR_SERPAPI_API_KEY/mcpHermes
hermes mcp add serpapi --url https://mcp.serpapi.com/YOUR_SERPAPI_API_KEY/mcpCodex
codex mcp add serpapi --url https://mcp.serpapi.com/YOUR_SERPAPI_API_KEY/mcpSelf-Hosting
git clone https://github.com/serpapi/serpapi-mcp.git
cd serpapi-mcp
uv sync && uv run src/server.pyConfigure Claude Desktop:
{
"mcpServers": {
"serpapi": {
"type": "http",
"url": "http://localhost:8000/YOUR_SERPAPI_API_KEY/mcp"
}
}
}Get your API key: serpapi.com/manage-api-key
Claude Desktop Extension (MCP Bundle)
For a local, one-click install, download the .mcpb bundle from the latest release (or build it as below) and open it with Claude Desktop (or drop it onto Settings → Extensions). Claude Desktop asks for your SerpApi API key during install, stores it as a sensitive setting, and runs the server locally over stdio. The bundle uses the MCPB uv runtime: it ships only the source, pyproject.toml and uv.lock, and Claude Desktop provisions Python and the locked dependencies with uv at install time, so nothing is vendored and one bundle works on macOS, Windows and Linux.
uv run mcpb/build.py # needs Node.js for the MCPB CLI; writes dist/serpapi-mcp-<version>.mcpbEverything bundle-related lives in mcpb/, plus .mcpbignore at the project root. The build regenerates the engine schemas from the SerpApi Playground (--no-rebuild-engines bundles engines/ from the working tree instead), validates mcpb/manifest.json, packs the git-tracked files minus .mcpbignore with the manifest at the bundle root, then installs it into a temp dir and starts it over stdio to make sure it works (--no-smoke skips that last step). The bundle is only built at release time: pushing a v<version> tag runs the release workflow, which runs the test suite and then deploys the hosted server, publishes the MCP Registry entry, and builds the bundle and attaches it to the GitHub release. Pull requests run the manifest and stdio entry point tests in tests/test_mcpb.py but do not pack a bundle.
The same stdio entry point works with any local MCP host that launches servers as a subprocess:
{
"mcpServers": {
"serpapi": {
"command": "uv",
"args": ["run", "--directory", "/path/to/serpapi-mcp", "--frozen", "--no-dev", "src/stdio.py"],
"env": { "SERPAPI_API_KEY": "YOUR_SERPAPI_API_KEY" }
}
}
}Authentication
Two methods are supported:
Path-based:
/YOUR_API_KEY/mcp(recommended)Header-based:
Authorization: Bearer YOUR_API_KEY
Examples:
# Path-based
curl "https://mcp.serpapi.com/your_key/mcp" -d '...'
# Header-based
curl "https://mcp.serpapi.com/mcp" -H "Authorization: Bearer your_key" -d '...'Search Tool
The MCP server has one main Search Tool that supports all SerpApi engines and result types. You can find all available parameters on the SerpApi API reference.
Engine parameter schemas are also exposed as MCP resources: serpapi://engines (index) and serpapi://engines/<engine>.
The parameters you can provide are specific for each API engine. Some sample parameters are provided below:
params.q(required): Search queryparams.engine: Search engine (default: "google_light")params.location: Geographic filterparams.output: Response format; omit for JSON (default), or set to"md"for Markdownmode: Response mode;"compact"removes metadata from JSON, while Markdown is returned unchanged...see other parameters on the SerpApi API reference
Examples:
{"name": "search", "arguments": {"params": {"q": "coffee shops", "location": "Austin, TX"}}}
{"name": "search", "arguments": {"params": {"q": "weather in London"}}}
{"name": "search", "arguments": {"params": {"q": "AAPL stock"}}}
{"name": "search", "arguments": {"params": {"q": "news"}, "mode": "compact"}}
{"name": "search", "arguments": {"params": {"q": "detailed search"}, "mode": "complete"}}
{"name": "search", "arguments": {"params": {"q": "news", "output": "md"}}}
{"name": "search", "arguments": {"params": {"engine": "amazon", "k": "mechanical keyboards", "amazon_domain": "amazon.com", "output": "md"}}}
{"name": "search", "arguments": {"params": {"engine": "google_scholar", "q": "retrieval augmented generation"}}}
{"name": "search", "arguments": {"params": {"engine": "youtube", "search_query": "how to make espresso"}}}
{"name": "search", "arguments": {"params": {"engine": "apple_app_store", "term": "habit tracker"}}}
{"name": "search", "arguments": {"params": {"engine": "ebay", "_nkw": "vintage mechanical keyboard"}}}Supported Engines: Google, Bing, Yahoo, DuckDuckGo, YouTube, eBay, and more (see serpapi://engines).
Result Types: Answer boxes, organic results, news, images, shopping - automatically detected and formatted.
Interactive UI (MCP Apps)
The default search tool returns JSON and is unchanged. For hosts that support the MCP Apps extension (SEP-1865), two opt-in tools render results as an interactive UI directly in the conversation, so the bulk SERP JSON never enters the model's context window:
search_table: organic results as a sortable, searchable table.search_dashboard: summary metrics, a source-breakdown chart, and a results table with a click-to-expand detail panel.
Both accept the same params as search. Hosts that don't support MCP Apps simply ignore these tools.
Preview them locally without an MCP host:
uv run fastmcp dev apps src/server.pyDevelopment
# Local development
uv sync && uv run src/server.py
# Docker
docker build -t serpapi-mcp . && docker run -p 8000:8000 serpapi-mcp
# Build the Claude Desktop extension (MCP Bundle); rebuilds engines, needs Node.js for the MCPB CLI
uv run mcpb/build.py
# Release: bump the version in pyproject.toml, server.json and mcpb/manifest.json, then tag it.
# Nothing ships on a plain push to main. The tag runs the release workflow, which runs the test
# suite and then deploys the hosted server, publishes server.json to the MCP Registry, and builds
# the MCP Bundle and attaches it to the GitHub release.
git tag v1.0.2 && git push origin v1.0.2
# Regenerate engine resources (Playground scrape)
python build-engines.py
# Testing with MCP Inspector
npx @modelcontextprotocol/inspector
# Configure: URL mcp.serpapi.com/YOUR_KEY/mcp, Transport "Streamable HTTP transport"Troubleshooting
"Missing API key": Include key in URL path
/{YOUR_KEY}/mcpor headerBearer YOUR_KEY"Invalid key": Verify at serpapi.com/dashboard
"Rate limit exceeded": Wait or upgrade your SerpApi plan
"No results": Try different query or engine
Contributing
Fork the repository
Create your feature branch:
git checkout -b feature/amazing-featureInstall dependencies:
uv installMake your changes
Commit changes:
git commit -m 'Add amazing feature'Push to branch:
git push origin feature/amazing-featureOpen a Pull Request
License
MIT License - see LICENSE file for details.
This server cannot be deployed
Maintenance
Related MCP Connectors
Official SerpApi MCP server for Google, Bing, and other search engines.
MCP server for Google search results via SERP API
Serper MCP — wraps the Serper Google Search API (serper.dev)
SerpApi MCP — wraps SerpApi (serpapi.com) search engines
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