mcp-searchapi
Provides Amazon product search, returning product details such as price, rating, ASIN, and sponsored status.
Provides general web search via Google, returning organic results with source and domain information.
Provides local business and place search via Google Maps, returning address, rating, coordinates, and open state.
Provides recent news search via Google News, returning articles with source and publication date.
Provides academic paper search via Google Scholar, returning publication, authors, and citation counts.
Provides video search via YouTube, returning channel, views, length, and publication time.
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., "@mcp-searchapiFind the latest job postings for data scientists"
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.
mcp-searchapi
An MCP server for SearchApi.io. Eight search engines exposed as discrete tools, returning trimmed structured results instead of raw SERP payloads.
npx -y mcp-searchapiWhy this exists
Two SearchApi MCP packages were already on npm when this was written. Both are single-version releases from mid-2025 that have not been updated since, neither has a test suite, and one of them targets SearchAPI**.site**, a different product. So this is not a third copy of the same thing:
One tool per engine, not one search tool with a mode flag. A model picks google_jobs correctly far more often than it picks search(engine="google_jobs"). Every parameter carries a description written as guidance, because those descriptions are the prompt the model actually reads.
Trimmed structured output. SearchApi returns results under a different key per engine (organic_results, local_results, shopping_results, videos, jobs), each with a different field set, and the payloads are large. Measured against live responses on 7 August 2026:
Tool | Raw payload | Returned at | Saved |
| 171,668 B | 2,507 B | 98.5% |
| 117,262 B | 4,391 B | 96.3% |
| 71,607 B | 3,172 B | 95.6% |
| 56,836 B | 3,587 B | 93.7% |
| 86,433 B | 7,772 B | 91.0% |
| 38,176 B | 4,221 B | 88.9% |
| 47,732 B | 7,718 B | 83.8% |
| 19,066 B | 5,813 B | 69.5% |
The percentage matters less than the ceiling: whatever the engine sends back, a page of results stays under 8KB. Handing a model 171KB of ad blocks, favicons and pagination tokens spends its context window on things it will never use.
Every result normalises to a common core (position, title, url, snippet) plus the extras that matter for that engine: price and rating for shopping, coordinates and opening state for maps, company and posting date for jobs, channel and view count for YouTube, citation counts for Scholar.
Related MCP server: evo-scry
Setup
Get a key at searchapi.io. The free tier is 100 searches a month.
Claude Desktop
~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows:
{
"mcpServers": {
"searchapi": {
"command": "npx",
"args": ["-y", "mcp-searchapi"],
"env": { "SEARCHAPI_API_KEY": "your-key" }
}
}
}Cursor
~/.cursor/mcp.json:
{
"mcpServers": {
"searchapi": {
"command": "npx",
"args": ["-y", "mcp-searchapi"],
"env": { "SEARCHAPI_API_KEY": "your-key" }
}
}
}VS Code
.vscode/mcp.json:
{
"servers": {
"searchapi": {
"type": "stdio",
"command": "npx",
"args": ["-y", "mcp-searchapi"],
"env": { "SEARCHAPI_API_KEY": "your-key" }
}
}
}Hosted
SEARCHAPI_API_KEY=your-key npx -y mcp-searchapi --http --port 3000Serves streamable HTTP at /mcp and a health check at /health. Stateless, so it scales horizontally without sticky sessions.
Tools
Tool | Engine | Use it for | Extra fields |
| General questions, fact-checking, finding sources |
| |
| Google News | Recent events, "what's happening with X" |
|
| Google Shopping | Price comparison, product availability |
|
| Google Jobs | Vacancies, hiring, job market |
|
| Google Scholar | Papers, citations, academic sources |
|
| Google Maps | Places, local business, "near me" |
|
| YouTube | Videos, tutorials, talks |
|
| Amazon | Amazon product lookups |
|
Parameters
query is required everywhere. limit (default 10, max 50) caps what comes back to the model. The rest are offered only on the engines that accept them:
Parameter | Meaning | Available on |
| Geo-target as | search, news, shopping, jobs, maps |
| Two-letter country code | search, news, shopping, maps, youtube, amazon |
| Two-letter language code | all except amazon |
| Results to request from the engine | search, news, shopping, scholar |
| Page number, from 1 | all except youtube |
google_jobs deliberately does not offer gl: the API rejects country codes on that engine (gl=ie returns HTTP 400 Unsupported value). Use location instead. Advertising a parameter the API will reject is worse than not having it, because the model has no way to discover the constraint.
Example
google_jobs(query: "backend engineer", location: "Dublin,Ireland", limit: 3){
"engine": "google_jobs",
"query": "backend engineer",
"totalResults": 10,
"results": [
{
"position": 1,
"title": "Backend Engineer",
"url": "https://...",
"company": "Example Ltd",
"location": "Dublin, Ireland",
"via": "LinkedIn",
"postedAt": "2 days ago",
"scheduleType": "Full-time",
"snippet": "..."
}
]
}totalResults reports what the engine returned, not what was kept, so the model can tell there is more available behind a higher limit.
Errors
Failures come back as tool errors with something actionable, not a bare status code:
Condition | Message |
Missing key | Server exits at startup rather than failing on the first call |
401 | Names |
429 | Says quota or rate limit, and notes the free tier is 100/month |
400 | Passes through the API's own message, for example the |
Timeout | Reports the elapsed limit; defaults to 30s |
No results | Not an error. Returns an empty |
Development
npm install
npm test # 77 tests, no network
npm run typecheck
npm run build
SEARCHAPI_API_KEY=... node scripts/smoke.mjs # end-to-end, costs 1 searchTests run against real captured API responses in test/fixtures/, one per engine plus an empty-result case, so they exercise the shapes the API actually returns rather than the shapes it was assumed to return. Nothing in npm test touches the network.
Adding an engine is a data change: append an entry to ENGINES in src/engines.ts with its result key, supported parameters and a normaliser. The server registers tools from that registry.
Licence
MIT
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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