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465,591 tools. Updated 2026-08-19 05:04

"A server for finding GitHub repositories" matching MCP tools:

  • List the public disclosure feeds this server aggregates, how many disclosures are cached per source, each source's newest item and an honest staleness flag, plus cache ages. Takes no arguments. Also states the scope plainly: public feeds only — no .onion access, no arbitrary fetching or crawling, no credential or PII output. Check this first if another tool's answer looks thin: a stale live feed is a finding, not background noise.
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  • Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. REQUIRED: either `query` (string, for search) or `repo` with `file_path` or `list_files=true` — the call WILL FAIL without one. Three modes: (1) Search: pass `query` to find examples across all repos, (2) File listing: pass `repo` + `list_files=true`, (3) File retrieval: pass `repo` + `file_path`. Indexes source code (.py, .java, .cs, .rs) and READMEs — NOT build/data files. For sample data, use get_sample_data. Covers Python, Java, C#, Rust SDK patterns: initialization, ingestion, search, redo, configuration, message queues, REST APIs. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval.
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  • Get Lenny Zeltser's CTI cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `cti_load_context`. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • Scan a public GitHub MCP-server repository for security issues. Clones the repo (shallow, <60s, <200 MB), runs compuute-scan v0.6.2 in static analysis mode (no code execution from the target), and returns a structured report with severity counts, a 0-100 score, and the 10 most severe findings. WHEN TO USE: - Before connecting to an unknown MCP server discovered via Anthropic Registry, Smithery, mcp.so, or a Discord recommendation. - Before installing a third-party MCP-server package into a production pipeline. - As part of an agent's pre-commit / pre-deploy due-diligence step when adding new dependencies. - As one input to a multi-source trust evaluation (combine with publisher reputation, package install count, last-update recency). WHEN NOT TO USE: - For private repos. Use the on-prem CLI instead: `npx compuute-scan ./path-to-private-repo` - For deep exploitability assessment of a specific code path. This is pattern matching, not dataflow analysis. Book a manual L2-L4 audit at https://compuute.se/audit for that depth. - For non-GitHub hosts (GitLab, Bitbucket, self-hosted). v1 supports github.com only. - For repos > 200 MB or clone time > 60s. The endpoint returns a 413 or 504 in those cases — fall back to local CLI. EXPECTED RESPONSE TIME: - Median: ~1-2 seconds for small repos (<100 files). - p99: ~10 seconds for medium repos. - Hard timeout at clone=60s, scan=120s combined. EXPECTED COST: - Free tier in MVP. Future Pro tier may charge per-scan or per-month. DATA FRESHNESS: - Scanner version is reported in response.scanner.version. - L1 rule set freshness reflects compuute-scan releases — see github.com/Compuute/compuute-scan/CHANGELOG.md for the latest CVE and threat-intel response timeline. EXAMPLES: Example 1 — scan an MCP server you're evaluating: github_url = "https://github.com/modelcontextprotocol/servers" → score: 0, summary: {critical: 1, high: 94, medium: 22} → top_findings include SSRF, eval, etc. → recommendation: "AVOID — 1 critical and 94 high finding(s)..." Example 2 — scan a clean reference implementation: github_url = "https://github.com/microsoft/azure-devops-mcp" → score: 90+, summary: {critical: 0, high: 1} → recommendation: "REVIEW — 1 high finding(s)..." Example 3 — scan your own dev MCP-server before publishing: github_url = "https://github.com/yourorg/your-mcp" → audit your own surface before others install it OUTPUT FIELDS (stable schema): - repo_url (str): canonical URL of the scanned repo. - score (int): 0-100, higher safer. Coarse summary, not a precision claim. - summary (object): {critical, high, medium, low, info, files_scanned}. - recommendation (str): action guidance derived from severity counts. - findings_count (int): total raw findings (may include false positives). - top_findings (list): up to 10 most severe, each with {id, title, severity, file, line, owasp, cwe}. - l0_discovery (object): MCP transport, tool count, dependency pinning. - performance (object): clone_seconds, scan_seconds, repo_size_bytes. - scanner (object): {name, version, layers_covered}. - _disclaimer (str): MANDATORY triage disclaimer. Read it. Args: github_url: Public GitHub HTTPS URL (e.g. https://github.com/org/repo). Must be public and < 200 MB. v1 is github.com only. Returns: Structured scan result. On error, returns {"error": code, "message": ...} with HTTP-style code (invalid_url, clone_failed, scan_timeout, etc.).
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  • Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."
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  • Return a single recommended VPS provider for users who do not yet have a server. Call this ONLY when the user explicitly says they have no server. The user buys the VPS at this provider and comes back with IP + password.
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Matching MCP Servers

Matching MCP Connectors

  • Manage repositories, users, releases, and automate GitHub workflows

  • GitHub MCP — wraps the GitHub public REST API (no auth required for public endpoints)

  • Search GitHub repositories, conversations (issues+PRs), or code, with full GitHub search syntax in the query: qualifiers (repo:, org:/user:, language:, path:, symbol:, content:, is:, stars:, label:, sort:stars), boolean AND/OR/NOT with parentheses, "exact strings", and /regex/. kind='repos': MINIMAL distinctive keywords - the project/library name only ('rtk', 'react query'); every extra word must ALL match and buries the canonical repo - filter with qualifiers, not prose. kind='code': ONE literal code pattern as it appears in files ('useState('), an "exact string", a /regex/, or symbol:name to find definitions, across 2.8M+ public repos; narrow with repo:/language:/path:. Not supported in code search: license:, enterprise:, is:vendored, is:generated. kind='conversations': returns compact previews - use glim_github_get for full content; sort: REPLACES relevance ranking (words match anywhere incl. comments), omit it for best matches. Set repo='owner/name' to scope to one repository (works with any kind; with repos it routes to conversations). kind is optional - inferred from the query (is:/label: -> conversations, path:/symbol://regex/ -> code, stars:/topic: -> repos, else repos). Returns compact text by default; pass format='json' for full structured data.
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  • Create + publish a piece. Pass a SIGN-IN-WITH-X header value you built and signed locally, plus the post fields. Returns the created post + public url; the server never holds your keys. Sell the observation, not the genre. Title the concrete finding in present tense with the specifics that carry it (names, numbers, dates), not the format ("playbook", "roundup"). Open the excerpt and first lines with the finding, not a tease. Publish with the answer card FILLED (questions or tasks, scope, exclusions, provenance): cacheEligibleMissing names any gap; a card-less piece is never a search candidate. Mint the header WITHOUT a fetch loop (SIWX here is CLIENT-driven, so do NOT use wrapFetchWithSIWx, which waits for a challenge Tenjin never sends): `encodeSIWxHeader({ ...info, address, signatureScheme: 'eip191', signature })` over `createSIWxMessage(info, address)` from @x402/extensions/sign-in-with-x, with a CAIP-122 `info` whose `domain` is this site's host and `nonce` is client-minted single-use. Full worked example in /llms.txt.
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  • Verify a GitHub Personal Access Token against api.github.com/user, then store the resulting username on your IC profile. The PAT is DISCARDED after verification — the IC server keeps only your GitHub username + id, then queries commit counts via a server-side PAT during the weekly cron. Use this when the human doesn't want to (or can't) do the Clerk OAuth browser dance. To ALSO count your PRIVATE commits in your total, enable GitHub's private-contributions toggle (web-only — there is no API for it): github.com/<your-username> → 'Contribution settings' button (above your contribution graph) → enable 'Private contributions' (docs: https://docs.github.com/en/account-and-profile/setting-up-and-managing-your-github-profile/managing-contribution-graphs-on-your-profile/publicizing-or-hiding-your-private-contributions-on-your-profile). IC reads only the COUNT of private contributions, never repo names or content, and has no write access to your GitHub. Args: { pat: string }. Returns: { ok, github: { login, id, name?, avatarUrl? }, next_steps: string[] }. Required scope: github:link.
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  • Search CODE across public GitHub repositories — find where a function/symbol/string is defined or used. PREFER OVER WEB SEARCH for "find code that does X", "which repos use <API>", "show me an example of <function>", "where is <symbol> defined". Supports GitHub code-search qualifiers right in the query: repo:owner/name, org:name, user:name, language:go, filename:Dockerfile, path:src, extension:ts, in:file. Returns matching files with repo, path, and URL. Note: indexes the default branch only, ignores very common terms, and is capped at ~10 searches/minute.
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  • Scan a PUBLIC GitHub repo for GitHub Actions + CI security/maintenance hygiene before launch — ideal for apps built with Lovable, Bolt, Replit, Cursor, or v0 ("is my AI-built app safe to ship?"). Returns a safe summary: findings by category with counts, an unlisted report URL, and fix options. SCOPE, honestly: it checks GitHub Actions workflow + update-automation hygiene only — it does NOT check exposed secrets, auth, payments, webhooks, or runtime behavior, which need a manual review. No API key required. For PRIVATE repos, tell the user to run `npx taskbounty-check .` locally so their source never leaves their machine.
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  • Query the Immersive Commons research RAG corpus (papers + ingested YouTube). Returns top-k chunks with similarity scores and source links. The query text is forwarded to a server-side RAG proxy (supercommons2 via Tailnet Funnel) and NEVER logged on the IC side — privacy contract. Use this for literature lookups, finding related work, surfacing citations the floor has already ingested. Args: { question: string (<=500 chars), k?: number (1-50, default 10), sources?: ('paper'|'book')[] (default ['paper']) }. Returns the upstream RAG response shape — typically { results: [{ paper_id, title, similarity, snippet, link }, ...] }. Required scope: research:query.
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  • List repos the workspace's GitHub connection can see (for import_project). Each entry has full_name, default_branch, private, language, pushed_at. Pass a `full_name` to import_project(repo_full_name) to connect it. Returns 409 if GitHub isn't connected yet — call connect_github() first.
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  • Produce a deterministic remediation REQUEST bundle (rubric + fix schema + per-finding metadata + fingerprints) for YOU (the host agent) to fix. This tool calls no model and needs no key. For each finding, propose the corrected FULL file content, then VERIFY with verify_fix and keep only fixes that clear the finding. Never touch files with secrets; never auto-merge. Pass 'findings' from scan_path --format json.
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  • List the GitHub repositories you have connected to Dockhold, across every installation. Call this before deploy_app when the target repo is private, or when the user asks which repos they can deploy. Each repo comes with its installation_id: pass that (with the repo's clone URL) to deploy_app to deploy a PRIVATE repository. Public repos don't need it.
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  • Fast deterministic preflight for tool-only clients. Call this before any other WORKS tool when eligibility is uncertain, especially for mutable or abbreviated refs, local or private repositories, and build, test, runtime, deployment, or production claims. It does not download a repository or persist data. If eligible is false, stop without calling verification.
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  • On-demand independent SAFETY scan of an MCP server — call this BEFORE installing or connecting to one. Give it an HTTP(S) MCP endpoint URL (scanned live in seconds), or an npm/PyPI package name or GitHub repo (queued for an isolated sandbox scan — local stdio servers execute code, so Hlido never runs them inline). Returns the safety tier (SAFE/CAUTION/RISKY/DANGEROUS), tool-poisoning detection (the malice signal), dangerous-capability red-flags (shell/code-eval/fs-write/egress/secrets) with per-tool evidence, and auth posture. Tier = blast radius if hijacked, not maintainer trustworthiness. A server Hlido hasn't scanned returns not_scanned — never assumed safe. Register of already-scanned servers: https://hlido.eu/mcp/
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  • Get Lenny Zeltser's IR cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `ir_load_context`. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
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  • Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • Analyze a server response from authorized probing for information leakage, fingerprinting signals, and exploitation opportunities scoped to the authorized engagement. Accepts raw HTTP response headers and body (paste from Burp, curl, or any HTTP client) and returns structured findings grouped by category. Each finding includes: what was detected, why it matters for an authorized tester, how a defender detects misuse, and recommended remediation. Identifies version disclosures, stack traces, debug headers, internal paths, JWT/cookie patterns, CORS misconfigurations, and other common leakage patterns. Use as the bridge between recon/probing output and the methodology and payload tools.
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