ContextFetch

ContextFetch MCP server

Web search and clean, LLM-ready Markdown for AI agents: $1 per 1,000 searches, and 25 a day free with no key and no signup.

claude mcp add contextfetch -- npx -y @contextfetch/mcp

That is the whole setup for Claude Code. Then ask your agent something that needs the web:

Search for how Postgres SKIP LOCKED works for job queues

contextfetch_search returns each page as Markdown, cut down to the passages that answer the query:

## 1. PostgreSQL Job Queues with SKIP LOCKED | CodeNotes

https://codenotes.tech/blog/postgresql-job-queues-with-skip-locked · score 1.000

FOR UPDATE SKIP LOCKED is useful because it lets many workers claim different rows without blocking on rows another worker has already locked. But it is only the claiming primitive. A production queue also needs the right schema, indexes, retry policy, stuck-job recovery, cleanup, monitoring, and replay-safe handlers. ...

11 tools: search, page to Markdown, find similar, research, answer, crawl, site map, balance, free key and auto top-up. Exa- and Tavily-compatible API underneath, at contextfetch.dev.

Install

Claude Code (one line, keyless):

claude mcp add contextfetch -- npx -y @contextfetch/mcp

With a paid key:

claude mcp add contextfetch -e CONTEXTFETCH_API_KEY=your_key -- npx -y @contextfetch/mcp

Cursor: add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project):

{

"mcpServers": { "contextfetch": { "command": "npx", "args": ["-y", "@contextfetch/mcp"], "env": { "CONTEXTFETCH_API_KEY": "your_key" } } } }

Windsurf: add to ~/.codeium/windsurf/mcp_config.json:

{

"mcpServers": { "contextfetch": { "command": "npx", "args": ["-y", "@contextfetch/mcp"], "env": { "CONTEXTFETCH_API_KEY": "your_key" } } } }

To use the free tier, drop the env block (or leave CONTEXTFETCH_API_KEY empty). The same JSON works in Claude Desktop's claude_desktop_config.json and in any other MCP client that launches stdio servers.

Requires Node.js 18 or newer.

Tools

All tools return Markdown text. Without a key, contextfetch_balance and contextfetch_auto_reload return a short message saying they need one, with the buy link. On the free tier, results start with a one-line notice showing how many free searches are left today. When the API reports them, a closing line shows latency (total and per stage: recall, fetch, rerank), whether the answer came from cache, and token savings (pruned tokens vs raw page tokens).

contextfetch_research sub-queries

Pass your own sub_queries (different angles on the question); the tool description tells the calling model to do so. If you omit them, the API derives them from query with fixed rules:

1. the query itself;
2. the query + documentation;
3. the query + benchmark when it mentions speed, performance, latency, memory or a comparison (vs, compare), otherwise the query + example.

A suffix the query already contains is skipped (so react useActionState example runs 2 searches, not 3). The whole research runs server-side in one /v1/research call that costs $1 per 1,000 sub-queries; a sub-query that fails is refunded and named in the header. If all fail, the tool returns the error.

Environment variables

Free tier and pricing

Pay as you go: top up from $10 (+10% from $100, +20% from $500). The balance never expires and one balance covers all your keys. Monthly plans and per-key limits are in the dashboard at contextfetch.dev/account.

When the balance or the free tier runs out (HTTP 402), the tool returns a one-click top-up link (Stripe: card, Apple Pay, Google Pay) and a line to pass on to your user. Then set CONTEXTFETCH_API_KEY as shown above.

Retries and connections

Connection failures before the request is sent (refused, DNS, connect timeout), HTTP 429 and HTTP 5xx are retried with exponential backoff and jitter (about 0.25-0.5 s, then 0.5-1 s), at most 3 attempts per API call and 30 seconds in total, retries included. A 429 or 5xx with a Retry-After header waits exactly that long, unless that would pass the 30 second budget. 400, 401, 402, 422 and other 4xx responses are never retried. A connection that drops after the request was sent is not retried either, since the search may already have been billed. Connections are pooled and kept alive by Node's built-in fetch (undici), so there is no extra HTTP dependency.

Errors

Errors never crash the server; they come back as tool results with isError: true and a plain explanation: invalid key (401), out of credits or free limit reached (402, lists the packs with their buy links), no saved card for auto-reload (409, with the buy link), URL not allowed (400, only public http(s) URLs), a page contextfetch_extract_url could not fetch (with the reason, such as HTTP 404), rate limited (429), server errors (5xx), network failures, and a 30 second limit per call (retries included).

Develop

npm install

npm run build # compiles src/ to dist/ and marks dist/index.js executable npm test # builds, then drives dist/index.js over stdio against a local mock API (no network) CONTEXTFETCH_API_BASE=http://localhost:8000 node dist/index.js

Publish

Publishing @contextfetch/mcp needs the npm organization contextfetch (create it at npmjs.com and add the publishing account as a member). Then npm publish from this folder; publishConfig.access is already public and prepublishOnly builds first.

License

MIT