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166,639 tools. Last updated 2026-06-02 16:51
"How to run a Python script in a sandboxed environment" matching MCP tools:
- Generates a voiceover from text using Hume Octave TTS. Audio uploaded to Spaces, signed URL returned (24h TTL by default). Charged in credits up-front based on script length (use quote_voiceover for a preview). Best for demo-video narration, tutorial audio, and any one-shot batch TTS. NOT a real-time conversational voice (use Hume EVI for that, different product). Voice options: pass voiceId for a specific Hume voice clone, or omit to use the deployment's default narrator (HUME_OCTAVE_VOICE_ID env var).Connector
- Answer 'how alike are these two places?' Mean-pool the 128-D GeoTessera embedding across each region's cells to get a centroid, then return the cosine similarity in [-1,1] (+1 = identical landscape, 0 = unrelated). Each region is {place} | {polygon_bbox} | {cells}. CPU-fetched embeddings — no GPU sidecar needed. Surfaces how many cells in each region actually carried a vector (coverage). When to use: Call to compare two areas at the level of overall land character (e.g. 'is this valley like that one?', 'find me somewhere that looks like X'). Degrades to a signed `inconclusive` (no number) when a region has no embedding-covered cells. For a single cell-to-cell vector cosine use `emem_compare`; for k-NN retrieval use `emem_find_similar`.Connector
- Get the actual Python code behind a community leaderboard strategy. Use after `browse_community`: pass an entry's `id` here to read its real `feature_engineering()` + `strategy_config()` source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to `one_shot` as `community_id`. Read-only, no signup needed. Args: community_id: The `id` of a community entry (from `browse_community`). Returns: dict with: id, title, username, description, symbol, timeframe, metrics {total_ret, win_rate, profit_factor, n_trades, mdd, sharpe_strat}, and `code` (the full Python source). SHOW the code to the user, and offer to deploy it via one_shot(community_id=...) or tweak it first.Connector
- Re-deploy skills WITHOUT changing any definitions. ⚠️ HEAVY OPERATION: regenerates MCP servers (Python code) for every skill, pushes each to A-Team Core, restarts connectors, and verifies tool discovery. Takes 30-120s depending on skill count. Use after connector restarts, Core hiccups, or stale state. For incremental changes, prefer ateam_patch (which updates + redeploys in one step).Connector
- Sample the signed distance from an in-script sdf.* field at a 3D point. Returns { distance, inside, aabb, kind }. Distance is in mm; negative = inside the surface, 0 = exactly on the surface, positive = outside. Use this to verify SDF composition before calling sdf.materialize (which is the expensive step). The script must bind the SdfField via sdf.bind('<name>', field) and pass that name as fieldName. Hint: pass either { file } or { code }, plus { fieldName, point: [x,y,z] }.Connector
Matching MCP Servers
- Flicense-qualityCmaintenanceEnables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.Last updated4
MCP Run Pythonofficial
Alicense-qualityFmaintenanceEnables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.Last updated192MIT
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Manage your Canvas coursework with quick access to courses, assignments, and grades. Track upcomin…
MCP server providing Pine Script v6 documentation. Enables AI to: Look up Pine Script functions and validate syntax Access official documentation for indicators, strategies, and visuals Understand Pine Script concepts (execution model, repainting, etc.) Generate correct v6 code with proper function references
- Get the connected user's profile, plan, onboarding state, team memberships, and note quota in a single call. Call this once at the start of a conversation so you can greet the user by first name, run the onboarding script only when needed, route notes to the right team space, and avoid suggesting Pro features to free users. Returns onboarding.completed (boolean) and onboarding.missing_steps (array of 'connect_mcp' | 'first_note'), which together tell you what, if any, setup is left. Exposes the user's email address and plan — same data the user sees in account settings, but never billing or token metadata. No parameters required.Connector
- List branches in a project. Requires at least Viewer role. Use max_results to bound the response size (default 100, max 1000). When the result is truncated, the response includes truncated=true and total_count so you know how many branches exist in total.Connector
- Estimate credit cost for a conversion BEFORE running it. Returns word count, page calculation (300 words/page), and a credit breakdown by format and template type. Use this when the user asks 'how much will this cost?' or when you suspect a conversion might exceed their balance — convert_document refuses to run if credits are insufficient, so estimating first is friendlier.Connector
- Create a new sncro session. Returns a session key and secret. Args: project_key: The project key from CLAUDE.md (registered at sncro.net) git_user: The current git username (for guest access control). If omitted or empty, the call is treated as a guest session — allowed only when the project owner has "Allow guest access" enabled. brief: If True, skip the first-run briefing (tool list, tips, mobile notes) and return a compact response. Pass this on the second and subsequent create_session calls in the same conversation, once you already know how to use the tools. After calling this, tell the user to paste the enable_url in their browser. Then use the returned session_key and session_secret with all other sncro tools. If no project key is available: tell the user to go to https://www.sncro.net/projects to register their project and get a key. It takes 30 seconds — sign in with GitHub, click "+ Add project", enter the domain, and copy the project key into CLAUDE.md.Connector
- Run this WITHOUT an API key to see what MCPSpend output looks like. Returns a synthetic cost snapshot identical in shape to get_today_cost + list_top_tools + get_usage_this_month. Use this to preview the product before signing up.Connector
- Read an HTML surface's body. HTML surfaces (Surface.kind="html") store mockup or full-page content as three text fields (html, css, js) rendered together inside a sandboxed iframe. Use `list_surfaces` to enumerate html surfaces in a workspace. Omit `surface_slug` to read the primary html surface; pass it to target a specific tab. Empty (never-written) html surfaces return { html:"", css:"", js:"" }. 404 when `surface_slug` doesn't match a live html surface. Requires viewer role.Connector
- List the four healthcare facility archetypes QSimHealth speaks to: ED, urgent care, walk-in clinic, appointment office. Returns one-line descriptions. Call describe_facility for detail on one type, or simulate_ed_demo to run a generic simulation.Connector
- Returns the calling account's id/email/role plus internal-use eligibility: whether the account is staff-flagged, which domains run free, and how a given target URL would be billed if you submitted a test now. Use this first when you bring TMV into a new project — it confirms the project's API key actually maps to the expected operator account.Connector
- Estimate credit cost for a conversion BEFORE running it. Returns word count, page calculation (300 words/page), and a credit breakdown by format and template type. Use this when the user asks 'how much will this cost?' or when you suspect a conversion might exceed their balance — convert_document refuses to run if credits are insufficient, so estimating first is friendlier.Connector
- POST /tools/tool_compute_sandbox/run — Executes Python 3.12 code in an isolated subprocess with a 5-second hard timeout. Input: {python_code: string, input_data: any (optional, bound as variable 'input_data')}. Output: {success, result, stdout (capped 50KB), execution_time_ms, error_type}. Return value: assign to 'result' variable. Pre-loaded: math, json, re, statistics, itertools, functools, collections, decimal, datetime, random, hashlib, base64. Blocked: import, open(), eval(), exec(), os, sys, network, class definitions, dunder attributes. error_type values: syntax_error | security_error | runtime_error | timeout_error. Cost: $0.1500 USDC per call.Connector
- Save a new note with learned knowledge or procedures. Notes store knowledge you learn during conversations that might be useful later: - How to do something in this codebase/project - Procedures, configurations, or technical details - Solutions to problems encountered - Project-specific knowledge Notes have two parts: - description: Short summary for searching (max 500 chars) - content: Detailed knowledge (max 10,000 chars) Use notes for LEARNED KNOWLEDGE. Use facts for TRUTHS ABOUT THE USER. Examples: - description: "How to deploy this Next.js project to Vercel" content: "1. Run 'vercel' command... 2. Configure environment variables..." - description: "Database migration process for this project" content: "Migrations are in supabase/migrations/. To apply: npx supabase db push..." SELF-LEARNING (scope="ai_client"): Your persistent memory across conversations. Save a note whenever you learn something worth remembering — don't wait, save as you go. Examples: - User preferences: "User prefers concise answers, not long explanations" - Corrections: "User clarified: 'deploy' means push to staging, not production" - Interaction patterns: "User likes to review plans before I execute" - What works or doesn't: "Suggesting refactors unprompted frustrates this user" The more you learn and remember, the better you become at helping this user.Connector
- Retry a failed simulation run. Resets an errored run back to 'created' status and triggers a new package build. The same run ID is reused. Only valid when status is 'error'. Returns 409 for any other state.Connector
- Reference info: the per-MB rate for a specific country. Call ONLY if the user explicitly asks about price for their destination (e.g. «how much in Japan?»). DO NOT call this during purchase — the user does not need to pick a country to buy. The eSIM works in all 192; rates are reference info, not a purchase gate.Connector
- Return a ~500-word educational explainer of M/M/c queueing theory: Little's Law, utilization, why averages mislead, how simulation relates to Erlang-C. No inputs. Use this when the user asks a conceptual 'why' or 'how does this work' question rather than asking for a number.Connector