MCP.Market

Fitter MCP server

by PxyUp·io.github.PxyUp/fitter·v1.8.3·133 stars
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Turn any website or API into structured JSON with LLM-authored declarative scraping configs.

B80/100grade B
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Safety scan
B80/100

full report

Adoption
Growing

133 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

Fitter tools

No tool declarations could be read from the package source. They show once the server is installed.

Public scan report

scanner v0.1.10 · 2026-10-31 · same rubric, same numbers if you re-run it

no findings
  • –Code scanpackage could not be scannedn/a
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 63 days ago12/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 80/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Fitter compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
80/100
higher than 60% of 4,461 AI and agents servers
GitHub stars
133
more than 95% of 2,713 AI and agents servers

Install Fitter in Claude Code, Cursor or VS Code

The registry entry has no remote endpoint or installable package.

What the publisher says

From the Fitter repository's README, as published. We do not edit it. Read it on GitHub

Fitter — web data for AI agents

Fitter turns any website or API into structured JSON — declaratively. One JSON/YAML config describes where the data lives (HTTP request, headless browser, file, static value) and what to extract (JSON paths, CSS selectors, XPath). No code, no brittle scraping scripts.

🚀 Try it in your browser — the real engine compiled to WebAssembly: live examples, a visual config builder, no install.

Because configs are plain data, LLMs can author them. The built-in MCP server lets Claude Code, Claude Desktop, or any MCP client write and run scraping pipelines on your machine, on demand:

"Get the top 5 HackerNews stories with titles and scores" → the model authors a fitter config, validates it, runs it locally, and gets clean JSON back.

One engine, five ways to use it:

Why fitter for AI agents?

  • Declarative & auditable — the agent produces a config you can read, save and re-run, not throwaway code
  • Local-first — all fetching happens on your machine; no third-party scraping API, no keys, no per-request billing
  • Batteries included — HTTP client, headless browser (Playwright/Chromium/Docker), JSON/HTML/XML/XPath/PDF parsing, pagination, cached references, host rate-limits — in a single static binary
  • Reusable — what the agent authored today becomes tomorrow's cron job or service config

How to use Fitter_MCP

Fitter MCP is a Model Context Protocol server (stdio transport) which lets any MCP client — Claude Code, Claude Desktop, IDE assistants, custom agents — run Fitter configs and get structured JSON back.

Quick start (Claude Desktop — one click)

Download fitter-mcp--.mcpb from the release page and open it — Claude Desktop installs the server automatically.

Quick start (Claude Code)

# 1. get the binary: download fitter_mcp_<version>-<os>-<arch> from the release page
#    https://github.com/PxyUp/fitter/releases — or build it from source:
go build -o fitter_mcp ./cmd/mcp

# 2. register it once, available in every project
claude mcp add fitter -s user -- "$(pwd)/fitter_mcp"

Then just ask:

Get the top 5 HackerNews stories with titles and scores using fitter

The model calls fitterconfigreference, authors a config, optionally checks it with fittervalidateconfig and executes it via fitterrun — all data fetching happens locally on your machine. For a ready-made pipeline try examples/configmorning_briefing.json:

Run examples/configmorningbriefing.json with fitter and give me the briefing

Register in Claude Desktop

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Grade history

  • 2026-10-31downgradeA → Bscore 80

Fitter: common questions

Is Fitter MCP server safe?
Mostly: it is graded B (80/100). Read the Fitter safety report
Does Fitter need an API key?
No secret keys are declared. It reads 7 settings from the environment.
Is Fitter maintained?
The last commit was 68 days ago (2026-08-29). The latest release is v1.8.3.
What can I use instead of Fitter?
Servers from other publishers that do the same job: Agent-Native Plan MCP server and Charlotte MCP server.
How does Fitter compare with other AI and agents MCP servers?
safety score 80/100 (higher than 60% of 4,461 AI and agents servers); github stars 133 (more than 95% of 2,713 AI and agents servers). Full comparison.

Alternatives to Fitter

Same job from other publishers: the closest match first, then the best rated.

  • Agent-Native Plan
    Structured visual plans and PR recaps with diagrams, prototypes, annotations, and sharing
    A
  • Charlotte
    Renders web pages into structured, agent-readable representations using headless Chromium.
    A