Safety-ranked open-source component discovery across npm, PyPI, GitHub and Hugging Face — for humans and AI agents. Never recommends a component whose license, security or health evidence is unsafe, missing or ambiguous.
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
- !README contains suspicious pattern: eval\s*\(
git clone https://github.com/Aniket-kr1030/ossfind{
"mcpServers": {
"ossfind": {
"command": "node",
"args": ["/path/to/ossfind/dist/index.js"],
"env": {
"OSSFIND_TELEMETRY_URL": "<ossfind_telemetry_url>"
}
}
}
}OSSFIND_TELEMETRY_URLMCP Servers overview
# ossfind — safety-ranked open-source component discovery
Given a query like *"http client"*, ossfind returns open-source components **ranked by whether you
can actually ship a product on them** — a blended, explainable score of **fit · license · security ·
maintenance health · integration effort** — served through **both a web UI and an MCP tool** over one
ranking engine.
Its core promise: **never recommend ("ship") a component whose safety evidence is unsafe, missing, or
ambiguous.** The engine fails *closed*.
**New here?** → [`GETTING_STARTED.md`](GETTING_STARTED.md) — install, try the offline demo, go live,
and connect it to an AI agent over MCP (Claude Code / Claude Desktop / Cursor config included), in
about five minutes.
## Command line
```bash
npm install -g ossfind
ossfind search "markdown parser"
ossfind search "http client" -e cargo -n 5
ossfind search "web framework" -e pypi --json # machine-readable
ossfind inspect marked # verified exports + import line
```
```
1. marked SHIP 92/100
MIT · 0 CVEs · OpenSSF 7.4
```
`-e/--ecosystem` npm · pypi · github · huggingface · cargo · rubygems · all — `-l/--license`
declares your project's license so incompatible results are ranked `AVOID` — `--json` for
scripting — `--no-color` (also honours `NO_COLOR`). Colour is disabled automatically when
stdout is not a terminal.
## Quick start (from source)
```bash
npm install
npm run typecheck && npm test # 586 tests, fully offline
npm run gates # 17 safety gates, each proven able to fail
npm run eval # relevance against the labelled query set (live)
```
Run the web app (offline demo mode, uses frozen fixtures):
```bash
OSSFIND_FIXTURES=1 npm run web # http://127.0.0.1:8787
```
By default, the web server binds exclusively to loopback (`127.0.0.1`).
- `HOST` — bind host (default `127.0.0.1`). Non-loopback hosts (e.g. `HOST=0.0.0.0`) require `OSSFIND_WEB_TOKEN` to be set; starting wide-open without a token is refused.
- `PORT` — server port (default `8787`).
- `OSSFIND_WEB_TOKEN` — optional Bearer token requiring `Authorization: Bearer <token>` on `/api/*` endpoints.
Run the MCP server (for AI agents):
```bash
OSSFIND_FIXTURES=1 npm run mcp # stdio MCP server exposing `search_components`
```
Drop `OSSFIND_FIXTURES=1` to hit live suppliers (npm registry, ecosyste.ms, deps.dev, OSV).
## Ecosystems (npm · PyPI · crates.io · RubyGems · GitHub · Hugging Face)
ossfind searches **npm** (default), **PyPI**, **crates.io** (Rust), **RubyGems**, **GitHub** repositories, **Hugging Face** models, or
**all six at once** (`ecosystem: "all"`) — one query, results from every ecosystem merged and
safety-ranked together, so you don't have to guess where the answer lives (e.g. "video generation" →
PyPI's `decord`, a GitHub AI-model repo, and a Hugging Face model in the same result set). Pick the
ecosystem with the web/MCP selector, the `ecosystem` MCP tool argument, or `&ecosystem=all` on
`/api/search`.
Discovery is **federated**: a `FederatedDiscoverer` composes multiple source adapters per query
(parallel, per-source error isolation + timeouts, results merged and deduped by id). Enrichment routes
each candidate by its own id prefix (`npm:`/`pypi:`/`cargo:`/`rubygems:`/`github:`/`huggingface:`), so a mixed batch is
enriched correctly per-source. The safety-ranking layer is the same for every source — ossfind owns
the ranking, not the corpus. GitHub and Hugging Face are what surface AI-model repos/models (diffusers,
CogVideo, …) that aren't on any package registry.
- **npm** needs no key — discovery uses the npm registry search API, with query expansion
(progressively shorter slices of the query, unioned) to recover the recall a conjunctive text
match loses. Optionally federate it with a local semantic index to bridge vocabulary the
registry cannot — `marked` says *parser* when you asked for a *renderer*:
```
INDEX_MAX=8000 INDEX_DB_PATH=.cache/index/npm.db npm run index:build npm
```
The same optional index federates crates.io, RubyGems and PyPI. When an index has not been
built, that ecosystem's search behaves exactly as before.
**It does not help everywhere, and the eval says where.** Measured on the labelled set:
npm and crates.io improve substantially (crates.io MRR 0.000 → 0.675, since crates.io's own
search ranks by name similarity and never returns `serde` for "serialization"). RubyGems is
neutral on MRR and slightly positive on recall. Rebuilding PyPI's index concentrated on the
top 8,000 packages measured slightly *worse* (0.611 → 0.597) than the broader 25,000-package
index, so the wider corpus stays — a hypothesis the harness rejected.
A RubyGems index originally measured much worse (MRR 0.500 → 0.250) by pushing `rails` out of
the enrichment shortlist. That was a shortlisting defect, not an index one, and is fixed: a
complete lexical match now counts as relevance evidence, so an adopted package whose
description contains every query word earns a slot regardless of its embedding score.
Measured on the labelled set, adding the index moved MRR 0.561 → 0.636, hit@3 60.5% → 67.4%
and noise@3 2.6% → 0.0%, with no per-query regressions — and made `marked` the top result for
*"markdown to html renderer"*, which no lexical probe can reach. Note that `npm run eval`
therefore depends on a locally built index; without one the numbers are the registry-only ones.
- **GitHub** uses the repo search API. Set an optional `GITHUB_TOKEN` in `.env.local` for higher rate
limits.
- **Hugging Face** needs no key — discovery uses the public models search API.
- **crates.io** (Rust) and **RubyGems** need no key — discovery uses their public search APIs,
with licence/vulnerability/health enrichment from ecosyste.ms, OSV and deps.dev like any package
ecosystem. crates.io ranks by name similarity, so "serialization" never returns `serde` from the
registry alone; federate a local index (`INDEX_MAX=6000 INDEX_DB_PATH=.cache/index/cargo.db npm
run index:build cargo`) to fix that.
- **Licence expressions**: an SPDX expression whose operands are *all* permissive resolves to a
permissive licence — Rust's near-universal `MIT OR Apache-2.0` is a real choice, not an audit
item. Any copyleft operand keeps the conservative treatment `G4` requires: `GPL-3.0 OR MIT`
never ships into a permissive project, and a `WITH` exception or unrecognized operand is left
for manual audit.
- **Health evidence is attributed only when the repository claim is corroborated.** A package's
repository URL is self-declared, and typosquats name the real project's repo to inherit its
OpenSSF score — five PyPI packages claiming `github.com/psf/requests` were reported SHIP 92/100
on the real project's 8.1. The claim is now checked against the package name and fails closed
(`G17`).
- **GitHub and Hugging Face components fail-closed to at most "caution"** (never "ship") — a raw repo's
or model's dependency CVEs can't be verified the way a published package's can; Hugging Face also has
no OpenSSF-style health score, so it relies on the existing missing-scorecard cap. License (SPDX) is
still enriched and gated for both.
- **PyPI** discovery uses a **self-hosted local index** by default (no key, no third-party service).
Build/refresh it once:
```
INDEX_MAX=50000 npm run index:build # top-N PyPI packages by downloads → .cache/index/pypi.db
```
The index is `node:sqlite` FTS5 (BM25) over name/description/keywords, semantically reranked by the
embedding model. Select the discovery source with `OSSFIND_PYPI_DISCOVERY=index|libraries|auto`
(default `auto`: local index if built, else libraries.io).
- **libraries.io is the fallback** for PyPI (used when no local index exists). It needs a free key in
a gitignored `.env.local` (`LIBRARY_IO_API_KEY=…`, `LIBRARIES_IO_API_KEY` also accepted), loaded via
`node --env-file=.env.local …`. Without index or key, PyPI discovery degrades to empty (never crashes).
## Live mode & caching
Live mode stores successful supplier responses on disk to reduce repeat requests and avoid supplier
rate limits. Fixture mode remains local and does not use this cache.
- `OSSFIND_CACHE_DIR` — cache directory (default `.cache/http/`).
- `OSSFIND_CACHE_TTL` — cache lifetime in seconds for discovery, license, and health data (default `3600`).
- `OSSFIND_SECURITY_TTL` — cache lifetime in seconds for OSV vulnerability data (default `300`).
- `OSSFIND_CONCURRENCY` — maximum concurrent upstream enrichment requests (default `4`).
- `OSSFIND_NO_CACHE=1` — disable the live-response cache.
Security responses may be up to `OSSFIND_SECURITY_TTL` seconds stale; tune this value down when
stricter vulnerability-data freshness is required.
Supplier APIs are free but rate-limited; review each supplier's terms before commercial use.
## Telemetry & Usage Metrics
ossfind includes an in-memory, privacy-preserving usage collector that tracks aggregate operational health and supplier rate limits.
### Local Inspection (Read-Only)
You can inspect usage metrics at any time without sending data anywhere:
- **MCP Tool:** Call `usage_stats` to receive the metrics snapshot and a formatted summary of top suppliers, cache hit rates, rate-limit headroom, and latency percentiles (p50/p95).
- **Web API:** Send `GET /api/usage` to retrieve the JSON snapshot. When `OSSFIND_WEB_TOKEN` is set, `/api/usage` requires the same `Authorization: Bearer <token>` header as `/api/search`.
### What Is Collected
- **Aggregate Supplier Counters:** Total requests, cache hits, cache misses, HTTP status class counts (`2xx`, `4xx`, `5xx`), 429 counts, error counts, and latest rate-limit headroom (`remaining`, `limit`, `reset`, `retryAfter`) per approved supplier host.
- **Search Operations:** Total searches served, ecosystem distribution (`npm`, `pypi`, `github`, `huggingface`), verdict distribution (`ship`, `cauWhat people ask about ossfind
What is Aniket-kr1030/ossfind?
+
Aniket-kr1030/ossfind is mcp servers for the Claude AI ecosystem. Safety-ranked open-source component discovery across npm, PyPI, GitHub and Hugging Face — for humans and AI agents. Never recommends a component whose license, security or health evidence is unsafe, missing or ambiguous. It has 0 GitHub stars and its last recorded update is dated 2026-09-06.
How do I install ossfind?
+
You can install ossfind by cloning the repository (https://github.com/Aniket-kr1030/ossfind) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is Aniket-kr1030/ossfind safe to use?
+
Our security agent has analyzed Aniket-kr1030/ossfind and assigned a Trust Score of 85/100 (tier: Trusted). See the full breakdown of passed checks and flags on this page.
Who maintains Aniket-kr1030/ossfind?
+
Aniket-kr1030/ossfind is maintained by Aniket-kr1030. The last recorded GitHub activity is dated 2026-09-06, with 0 open issues.
Are there alternatives to ossfind?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
Deploy ossfind to your cloud
Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.
Maintain this repo? Add a badge to your README
Drop the badge into your GitHub README to show it's tracked on ClaudeWave. Each badge links back to this page and reflects the live Trust Score.
[](https://claudewave.com/repo/aniket-kr1030-ossfind)<a href="https://claudewave.com/repo/aniket-kr1030-ossfind"><img src="https://claudewave.com/api/badge/aniket-kr1030-ossfind" alt="Featured on ClaudeWave: Aniket-kr1030/ossfind" width="320" height="64" /></a>More MCP Servers
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
An open-source AI agent that brings the power of Gemini directly into your terminal.
Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface
The fastest path to AI-powered full stack observability, even for lean teams.
🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!