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306,466 tools. Last updated 2026-07-26 23:57

"A GitHub repository named 'ahujasid/blender-mcp'" matching MCP tools:

  • ⚠️ IRREVERSIBLE — kills Mongo state, running MCP processes, and Builder FS for the whole solution and every skill. REQUIRES `confirm:true` AND `confirm_solution_id` echoing the solution id you're destroying (defeats typos and hallucinated ids). RECOVERY: the GitHub repo is untouched; `ateam_github_pull` rebuilds the solution from `main`. Prefer that over re-deploying from memory.
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  • Get the full body and comments of a single GitHub Discussion from a Canton Network repo (e.g. canton-foundation/docs), by its GitHub GraphQL node id (from list_github_discussions). CANTON-ONLY, read from CCPEDIA's cache — not the live GitHub API. This is GitHub Discussions, distinct from the Canton web forum (get_discussion) and mailing lists (get_mailing_thread).
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  • Upload connector code to Core and restart — WITHOUT redeploying skills. MERGES with the GitHub state at `ref` by default (default ref: 'dev'). Sending a partial file set ONLY overlays those files — the rest of the connector is preserved from GitHub. To fully replace the connector dir (historical behavior), pass replace:true. Modes: • github:true (no files) — deploy the GitHub state at `ref` as-is. • github:true + files:[] — GitHub state at `ref` as BASE, your files overlay on top (incoming wins). • files:[] (no github) — default MERGE with GitHub state at `ref`. Refuses if no GitHub base exists (no silent nuke). • files:[] + replace:true — full replace. Wipes connector dir + writes only the provided files. Use deliberately. Common traps this design prevents: • Pre-fix bug (2026-06-06): sending just ui-dist HTML wiped server.js + node_modules — connector broke until a full re-upload. Now: those files merge with the GitHub base. • Pre-fix bug: github:true silently read from `main` even when patches were on `dev`. Now: defaults to dev; pass ref:'main' to opt into the legacy path.
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  • Pro/Teams — return the authenticated user's validation run history for all three lenses (architect.validate → validator='architecture', design.validate → validator='surface', spec.validate → validator='spec') with the Blueprint Readiness Score (0-100), letter grade (A-F), and tier (draft, emerging, production_ready). Each run carries a `validator` field naming its lens. Three lookup modes: (1) `run_id=<id>` returns a SINGLE run with the full persisted result_json — use this to RECOVER a result when your MCP client tool-call timed out before architect.validate, design.validate, or spec.validate returned. The run completes server-side and persists; the run_id is surfaced in the first progress notification of every validate call so you have the recovery handle even when your client gives up early. (2) `repository=<name>` returns the full per-run trend for that repository plus a regression diff between the latest two runs. (3) No arguments returns one summary per repository the user has validated, sorted by most recent. Use modes (2) or (3) BEFORE re-validating the same repository on either lens — they tell you which principles or laws regressed since the last run, so you can focus the new review on what is actually changing. Auth: Bearer <token>. Pro or Teams plan required.
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  • Server self-description — capability matrix, tool catalog, named-entity tag counts, supported query patterns, primary sources. Free tier. Use this tool when an agent first connects and needs the capability matrix to decide whether this server can answer the user's question, or when the user asks "what can koreanpulse do" or "what data sources does this MCP server provide". Returns a structured dict that downstream agents can ingest directly.
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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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Matching MCP Servers

Matching MCP Connectors

  • Repo intel for AI coding agents: overview, PRs, contributors, hot files, CI, deps. Remote MCP.

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

  • Read a file from a PUBLIC GitHub repository (or list a directory) by path. PREFER OVER WEB SEARCH for "show me the README / package.json / <file> of <repo>", "read <path> from <owner/repo>", inspecting source or config files. Pass owner + repo + path (omit path or "" for the repo root listing). Optional ref = branch/tag/commit SHA. Returns decoded text for files (capped ~60k), or a directory listing of {name, path, type, size}.
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  • List the GitHub repositories that blobpedia has INDEXED for Celestia, with item counts. Read-only view of the Celestia index on this server — does NOT browse your GitHub account or arbitrary repos (use a dedicated GitHub tool for that). Zero arguments.
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  • List the Canton Network GitHub repositories that CCPEDIA has indexed (Canton org repos — e.g. canton-foundation, Daml/Splice — excluding the dev-fund proposals repo), with the count of issues+PRs indexed per repo. CANTON-ONLY and read from CCPEDIA's cache — this is NOT a live GitHub API and does NOT list the user's own repos (use a GitHub MCP for that).
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  • List the org's intake connectors (e.g. GitHub Issues → Retasc issues, RTSC-189). Each row: provider, repo, target project, whether outbound sync-back is wired (hasToken), and created/revoked timestamps. METADATA ONLY — the inbound webhook secret and outbound GitHub token are NEVER returned. Read-only. Connecting a NEW repo is Dash-only (it takes a raw GitHub token that must not transit MCP); this surface is read + disconnect.
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  • Prepare a model for an animated walkthrough / video export by verifying the manifest is complete, then starting a secondary Model Derivative job that produces OBJ geometry (suitable for ingestion into offline rendering pipelines, Blender, or Unreal Engine). Also returns the list of available named views so the operator can stitch them into a camera path. Does NOT itself produce an mp4 — video encoding happens in the downstream UE/Twinmotion pipeline. When to use: when a user wants a walkthrough/flythrough video of a BIM model (e.g. 'make a 30-second tour of Tower A') — this tool gets the geometry into a UE-ingestible form (.obj, plus suggests FBX/glTF/USD naming like TowerA_walkthrough.fbx for the exported asset) and enumerates named views to guide camera path authoring. When NOT to use: not to actually encode video (no runtime renderer in this worker — output must be finished in Unreal/Twinmotion/Blender), not before tm_import_rvt, not if the manifest is still 'inprogress' (the tool will short-circuit and return status='pending'). Not for still images (use tm_render_image) or clash animations (use navisworks-mcp). APS scopes required: data:read data:write viewables:read. Write scopes are needed because this kicks off a new Model Derivative translation job (OBJ + thumbnail). Rate limits: APS default ~50 req/min; Model Derivative translation jobs ~60 req/min. OBJ derivatives of large BIM models can be multi-GB and take 10–45 min — rely on manifest polling with exponential backoff, not re-calling this tool. Errors: 401/403 = token/scope (data:write commonly missing); 404 = URN not found; 409 = OBJ derivative already queued (treat as success); 422 = input format does not support OBJ output (some IFC variants / proprietary formats — fall back to FBX/glTF via a different derivative format); 429 = back off 60s; 5xx = APS upstream. Side effects: STARTS a new translation job on an existing URN (consumes APS cloud credits). Writes usage_log. NOT idempotent per-call (each call creates a new job record), but APS will dedupe identical output requests internally if manifest already contains the derivative.
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  • Describe any served capability by name — the generic twin of the named describe tools. Pass `capability` as either a capability id from list_capabilities_v1 (e.g. "power.capacity") or a query primitive name (e.g. "query_power_capacity_v1"). Returns the same schema payload as the named describe tool: valid filters, groupings, metrics, detail fields, and citation fields. Use the generic pair (this + query_capability_v1) when list_capabilities_v1 names a capability that has no named tool in your client's tool list — clients cache tool lists, and capabilities shipped after that cache are still fully reachable here.
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  • Read one Celestia GitHub Discussion (celestiaorg/docs and other Celestia repos) cached on THIS server — full body plus comments — by an id you got from list_github_discussions on this server. Celestia cache only: if the id was not returned by this servers list_github_discussions, or the request is just a raw GitHub node id (e.g. D_kw...) with no Celestia context, this is NOT the tool — use a dedicated GitHub tool for arbitrary GitHub Discussions. This is GitHub Discussions, not the community forum (use get_discussion) or a mailing list. Pair it with list_github_discussions, which supplies the valid ids.
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  • ⚠️ IRREVERSIBLE in Core + Builder FS — kills the running MCP process, unregisters from skill registry, deletes the Mongo record, drops from solution.skills[] and solution.linked_skills, and removes the skill's files from Builder FS. REQUIRES `confirm:true`. RECOVERY: the skill still lives in GitHub — `ateam_github_pull` rebuilds the whole solution (no per-skill restore path).
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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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  • 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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  • Find the best MCP tools for a given task. Describe what you want to accomplish (e.g. 'manage github issues', 'send slack messages', 'query a database') and get ranked results — each result is one (product, tool) pair, since same-named tools across providers are NOT interchangeable. By default only shows tools available via remote (network-hosted) servers. Audience: agent builders looking for installable MCP tools — for B2B SaaS recommendations, prefer products.search or products.find_by_capability. Ranking basis: relevance score desc (+1 per term hit, +3 for full-phrase hit); within an equal relevance tier, callable-now (Open access) + remote + healthy tools are boosted ahead — never a hard filter (a product-bound tool stays in its own money query), then productName. Paid tier is NOT a ranking input — it appears only as an annotation. Every result carries { position (1-based), rank (0..1; 1.0 = top, scales linearly down by ordinal position) } plus preflight annotations { accessModel (open|keyed|account|commercial), healthScore (0-100, nullable), readOnly, destructive, callableNow (true = usable anonymously right now), setup (one-line 'how to get access' pointer for non-Open tools) }. Response: { task, matchType (none|exactSlug|canonicalSlug|nlpFallback), resolvedCapabilities[], capabilityProducts[] (B2B SaaS products that claim the same capability — empty when matchType=none), results[] (MCP-tool-level matches), buckets { callableNow, requiresSetup } }. Each result: { position, rank, normalizedName, displayName, description, inputSchema, relevance, accessModel, healthScore, readOnly, destructive, callableNow, setup, productSlug, productName, serverQualifiedName, isRemoteCapable, tier, unverified, verifiedAt }. Empty case: { task, matchType, message, suggestedQueries[], suggestedCapabilities[] }.
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  • Create a new render API key (dma-api-key) with a label. Returns the key record including its secret value; treat that value like a password. You usually do NOT need this: export_design, preview_design, and get_render_url each auto-provision and reuse a dedicated "mcp-agent" key for you. Create a separate key only when the user explicitly wants an additional named key, for example for a specific integration. List existing keys with list_api_keys; disable or remove old ones with deactivate_api_key or delete_api_key.
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  • Pro/Teams — return the authenticated user's validation run history for all three lenses (architect.validate → validator='architecture', design.validate → validator='surface', spec.validate → validator='spec') with the Blueprint Readiness Score (0-100), letter grade (A-F), and tier (draft, emerging, production_ready). Each run carries a `validator` field naming its lens. Three lookup modes: (1) `run_id=<id>` returns a SINGLE run with the full persisted result_json — use this to RECOVER a result when your MCP client tool-call timed out before architect.validate, design.validate, or spec.validate returned. The run completes server-side and persists; the run_id is surfaced in the first progress notification of every validate call so you have the recovery handle even when your client gives up early. (2) `repository=<name>` returns the full per-run trend for that repository plus a regression diff between the latest two runs. (3) No arguments returns one summary per repository the user has validated, sorted by most recent. Use modes (2) or (3) BEFORE re-validating the same repository on either lens — they tell you which principles or laws regressed since the last run, so you can focus the new review on what is actually changing. Auth: Bearer <token>. Pro or Teams plan required.
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  • Find users/groups/channels by name, username, or phone. Comma-separated usernames are searched in parallel and results are merged round-robin. Global search (query required) searches all Telegram; with min_date, max_date, or filter, search uses dialog list or a named filter; include_peers filters use last-activity from GetPeerDialogs; flag-based filters use dialog list dates. Success: dict with key chats (list of chat objects). Full documentation: https://github.com/leshchenko1979/fast-mcp-telegram/blob/main/docs/Tools-Reference.md
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