by PxyUp
New way for collect information from the API's/Websites
# Add to your Claude Code skills
git clone https://github.com/PxyUp/fitterLast scanned: 7/25/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-07-25T06:18:27.828Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}fitter is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by PxyUp. New way for collect information from the API's/Websites. It has 132 GitHub stars.
Yes. fitter passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/PxyUp/fitter" and add it to your Claude Code skills directory (see the Installation section above).
fitter is primarily written in Go. It is open-source under PxyUp on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh fitter against similar tools.
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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:
| 🤖 Fitter MCP | MCP server exposing fitter to Claude Code, Claude Desktop and any MCP client |
| 🧠 Fitter Agent | AI-powered CLI: natural language → config → executed result |
| 🖥 Fitter CLI | run configs locally for test/debug/home usage |
| 📦 Fitter Lib | embed the engine in your own Go program |
| ⚙️ Fitter | long-running service mode with scheduling & notifications |
Why fitter for AI agents?
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.
Download fitter-mcp-<os>-<arch>.mcpb from the release page and open it — Claude Desktop installs the server automatically.
# 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 fitter_config_reference, authors a config, optionally checks it with fitter_validate_config and executes it via fitter_run — all data fetching happens locally on your machine. For a ready-made pipeline try examples/config_morning_briefing.json:
Run examples/config_morning_briefing.json with fitter and give me the briefing
{
"mcpServers": {
"fitter": {
"command": "/path/to/fitter_mcp"
}
}
}
| Tool | Description |
|---|---|
fitter_run |
Run a Fitter config passed inline (JSON or YAML string) and return the extracted data as JSON. Accepts an optional input value available in the config via {{{FromInput=.}}} / {{{FromInput=json.path}}} |
fitter_run_file |
Same as fitter_run but reads the config from a local .json/.yaml file |
fitter_run_url |
Same as fitter_run but downloads the config from an HTTP(S) URL, e.g. a raw GitHub link |
fitter_validate_config |
Validate a config without executing it (structure, response_type, connector data source, model). Useful while iterating on a config |
fitter_config_reference |
Return a condensed reference of the whole config format (connectors, parsers, model/field schema, placeholders, notifiers, references, limits) with working examples, so the model can author configs without external docs |
The reference is also exposed as MCP resource fitter://config-reference for clients that support resources.
The config format is exactly the same as for Fitter_CLI: a top-level object with item (required), limits and references. Notifiers work too (the result is additionally pushed to http/telegram/redis/file/console); trigger_config and http_server are service-mode only and are ignored in MCP calls.
By default fitter_mcp talks stdio. Pass --http to serve the streamable HTTP transport instead — for a shared team server, a container, or any remote deployment:
# serve MCP at http://<host>:8080/mcp (health probe at /healthz)
FITTER_MCP_AUTH_TOKEN=my-secret fitter_mcp --http :8080
# register the remote endpoint in Claude Code
claude mcp add --transport http fitter http://localhost:8080/mcp --header "Authorization: Bearer my-secret"
--http <addr> (env FITTER_MCP_HTTP_ADDR) — listen address; stdio mode when emptyFITTER_MCP_AUTH_TOKEN — when set, every /mcp request must send Authorization: Bearer <token>; without it the endpoint is unauthenticated, so bind to localhost or put it behind a proxy--stateless (env FITTER_MCP_STATELESS=true) — no per-session state, so replicas can sit behind a load balancer without sticky sessionsThe server shuts down gracefully on SIGINT/SIGTERM.
A slim multi-arch image (linux/amd64 + linux/arm64) ships with every release:
# hosted HTTP mode
docker run --rm -p 8080:8080 \
-e FITTER_MCP_HTTP_ADDR=:8080 \
-e FITTER_MCP_AUTH_TOKEN=my-secret \
ghcr.io/pxyup/fitter-mcp:latest
# or stdio mode, spawned by the MCP client
claude mcp add fitter -s user -- docker run --rm -i ghcr.io/pxyup/fitter-mcp:latest
The slim image contains only the fitter binary and CA certificates: server/static/file connectors work, browser connectors (chromium/docker/playwright) do not.
For browser-based configs use the playwright variant, which bundles Playwright with Chromium, Firefox and WebKit (matched to the playwright-go version fitter is built against, so no "install": true is needed in configs):
docker run --rm -i ghcr.io/pxyup/fitter-mcp:playwright # stdio mode
# per-release tag: ghcr.io/pxyup/fitter-mcp:vX.Y.Z-playwright
It is built from Dockerfile.mcp-playwright; build with --build-arg PLAYWRIGHT_BROWSERS=chromium for a smaller Chromium-only image.
Both images ship fitter_cli, so the one-time OAuth2 login can run inside the container. Store the token on a volume mounted at /tokens (pre-created writable in the image) and share it with the MCP server:
# one-time login, device flow: no ports needed — open the printed url on any device
docker run --rm -it -v fitter-tokens:/tokens --entrypoint fitter_cli \
ghcr.io/pxyup/fitter-mcp:latest \
auth --provider github --client-id <ID> --client-secret <SECRET> --token-file /tokens/github.json
# or browser flow (device flow not enabled for the app): publish the callback port and
# bind on 0.0.0.0 so the published port reaches the listener; the browser still visits 127.0.0.1
docker run --rm -it -p 8988:8988 -e FITTER_AUTH_LISTEN=0.0.0.0 \
-v fitter-tokens:/tokens --entrypoint fitter_cli ghcr.io/pxyup/fitter-mcp:latest \
auth --provider github --client-id <ID> --client-secret <SECRET> --token-file /tokens/github.json
# then run the MCP server with the same volume; configs reference "token_file": "/tokens/github.json"
# stdio mode (spawned by the MCP client, no port):
docker run --rm -i -v fitter-tokens:/tokens ghcr.io/pxyup/fitter-mcp:latest
# hosted HTTP mode (MCP endpoint on 8080, like the run examples above):
docker run --rm -p 8080:8080 -v fitter-tokens:/tokens \
-e FITTER_MCP_HTTP_ADDR=:8080 \
-e FITTER_MCP_AUTH_TOKEN=my-secret \
ghcr.io/pxyup/fitter-mcp:latest
Note: 8988 is only for the one-time browser-flow login; the MCP server itself needs no port in stdio mode and only 8080 in hosted HTTP mode.
Browser sessions need the playwright image (the slim one has no browsers). The one-time headed login needs a display, so run it on the host, then bind-mount the session dir into the container (the image pre-creates a writable /sessions):
# on the host: log in once, save the session
fitter_cli browser-login --url https://example.com/login --storage-state ~/.fitter/sessions/example.json
# run the MCP server with the sessions dir mounted; configs reference "storage_state_file": "/sessions/example.json"
docker run --rm -i -v ~/.fitter/sessions:/sessions ghcr.io/pxyup/fitter-mcp:playwright
Use a bind mount (not a named v