"Finding tasks for large language model agents" matching MCP tools:

• text_to_speech

  Sats4AI - Bitcoin-Powered AI Tools

  Text-to-speech with 3 tiers: OmniVoice Global (602+ languages including Yoruba, Bengali, Cebuano, Twi, zero-shot voice cloning, 100 chars/sat — use 'language' parameter with ISO code), Inworld Premium (#1 ranked TTS ELO 1217, emotion control, 40+ languages, 50 chars/sat), Minimax Studio (voice cloning from reference clip, 40+ languages, 10 chars/sat). Adjustable speed (0.5-2.0x). Returns audio URL. Pay with Bitcoin Lightning — no API key or signup needed. When NOT to use: not for phone calls (use place_call for one-shot broadcasts, ai_call for AI voice agents, or open_voice_bridge to drive the call with your own LLM). For rare/underserved languages (Yoruba, Twi, Marathi, Cebuano, etc.), pick OmniVoice Global via language= — Inworld/Minimax don't cover these. Requires create_payment with toolName='text_to_speech'.

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• agents_update_from_template

  dialogbrain

  Update a forked agent's instructions (prompt) to the latest version of the system template it was created from. Use when the platform has improved a template and the user wants their forked agent to pick up the new prompt. This OVERWRITES the agent's prompt_text with the template's current prompt — any customizations to the prompt are replaced (recoverable via prompt history). Tool/model/execution settings are NOT changed. Only works on agents forked from a template (not from-scratch agents or templates themselves).

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• register_agent

  Molt2Meet

  Register to dispatch physical-world tasks. No existing account needed. Returns an API key (m2m_...) required for all subsequent tools — store it securely, shown only once. For OpenClaw agents: provide agentFramework='openclaw', your callbackUrl (e.g. http://host:port/hooks), and callbackSecret (your hooks.token). Molt2Meet will then push task status events directly to you via /hooks/wake or /hooks/agent. Before registering, call get_legal_documents to read the terms you are accepting. Requires: nothing. Next: dispatch_physical_task to dispatch a task, or list_service_categories to explore options first.

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• query_tasks

  cnvs.app

  Read tasks from a 'todo' board with server-side filtering — handy for 'what's overdue?' / 'what's assigned to X?' without pulling the whole board. All filters are optional and AND together: `assignee` (exact match), `priority` ('H'|'M'|'L'), `done` (boolean), `overdue` (true → due_date strictly before today, not done), `due_before` / `due_after` (ISO date window on due_date). Returns `{ boardId, mode, tasks }` — tasks ordered by sort, each with the same fields as `list_tasks`.

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• tm_import_rvt

  Twinmotion MCP

  Import a Revit/BIM model into the Twinmotion visualization pipeline: downloads the source file from a public URL, uploads it to an APS OSS transient bucket, and kicks off an SVF2 + thumbnail translation job. Returns the base64 URN (project_id) used by every other tm_* tool. When to use: when a user wants to prepare a Revit (.rvt), IFC (.ifc), or other BIM/CAD model for real-time visualization in Unreal Engine / Twinmotion — typically the first step before rendering stills, defining scenes, or exporting FBX/glTF/OBJ geometry for a UE import. Also use when you need thumbnails or view metadata from a source file that has not yet been translated by APS. When NOT to use: not for MEP clash review (use navisworks-mcp), not for quantity takeoff or cost estimation (use qto-mcp), not for Twinmotion presets editing — Twinmotion itself has no public REST API, so scene/material authoring must happen manually in the UE editor after FBX/USD export. APS scopes required: data:read data:write data:create bucket:read bucket:create viewables:read. Uses Model Derivative API (translation) + OSS (upload). Twinmotion has no public REST API; all automation is APS Model Derivative + manual Unreal Engine export. Rate limits: APS default ~50 req/min per app per endpoint; Model Derivative translation jobs ~60 req/min; large .rvt/.nwd/.ifc files are often multi-GB and translation can take 5–60 min — poll the manifest with exponential backoff (start 5s, cap 60s) rather than retrying this tool. Worker request ceiling is ~100MB body; extremely large files may need signed-URL upload instead. Errors: 401 = APS token failed (check APS_CLIENT_ID/APS_CLIENT_SECRET, re-auth); 403 = scope missing (bucket:create/data:write not granted — have user re-consent); 404 = file_url unreachable; 409 = bucket key collision (rare — retry, tool uses timestamp); 413/507 = file too large for worker memory (advise signed-URL upload); 422 = unsupported source format (only Autodesk-accepted types: rvt, ifc, nwd, dwg, dgn, 3dm, stp, etc.); 429 = back off 60s before retrying; 5xx = APS upstream outage, retry with backoff. Side effects: CREATES a new transient OSS bucket (scanbim-viz-<timestamp>, auto-expires in 24h), CREATES an object in OSS, STARTS a translation job consuming APS cloud credits. NOT idempotent — each call creates a new bucket + URN. Writes a row to usage_log D1 table.

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• setup_agent_fleet

  mcp

  Complete one-shot setup: validates prerequisites, creates a controller VM + worker VMs, auto-creates a public HTTPS URL on port 7070, seeds a starter ROADMAP.md into the repo if absent, and returns the trigger token. Call this when a user says 'set up autocoding agents for my repo' or 'I want agents to work on my codebase'. HOW THE AGENT WORKS: each worker runs Claude Code inside the repo, implements one task, runs the test suite, and opens a pull request. It excels at focused, single-PR, testable units of work — add an endpoint, write tests for a module, fix a specific bug, add a UI page — and is poor at vague/large tasks, design decisions, or anything needing external credentials. TASK FORMAT (strict, one line each): `- [ ] **Title** — short description *(agent-ready)*` — the `- [ ]` checkbox, `**bold title**`, ` — ` separator, and `*(agent-ready)*` are ALL required; `##` headings and plain bullets are ignored. After this returns, the user needs to: (1) authorize the fleet by running the authorize.sh one-liner it returns (it runs `claude setup-token` for a long-lived token installed on the controller) — agents use the user's existing Claude Max/Pro subscription, NOT an API key. This is a shell command the USER runs in their own terminal; do NOT try to read or push the user's credentials yourself. The controller takes ~7 min to boot, so PREFER to poll get_agent_status until it reports the controller is reachable and present the authorize command only once it's ready — that way the user doesn't run it into a long wait. (The command also waits on its own, showing a live progress counter, so a user who runs it early is fine too.) (2) add well-scoped tasks in the format above to ROADMAP.md; (3) call trigger_agent_batch.

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• get_arena_leaderboard

  CoinRithm Agent Trading

  The public Agent Arena: opted-in agents ranked by total realized PnL (mUSD) across spot, futures, and prediction markets, with per-venue breakdown and win rate. Only agents with at least minDecidedTrades decided (win+loss) trades rank (currently 3 — echoed in the response); demo/house agents seed the board until live agents qualify. Rows also carry a 44-day sparkline, badges, rankDelta, biggestWinMusd, and the self-reported model label. Pass window='7d'|'30d' for the weekly/monthly board — re-ranked by PnL realized inside the window (badges/biggestWin and the min-decided gate stay all-time). Use it to see the field and where you stand — pair with get_performance (your own scorecard) and get_arena_agent (drill into one handle). Public data: agent names + performance only. Paper trading only — virtual funds (50,000 mUSD). Not financial advice.

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• company_search

  Drillr — The financial MCP for AI agents

  Use for qualitative company discovery (industry, business model, supply chain, competitors, management background). For numerical screening (revenue, margins, ratios, growth rates) use run_sql on company_snapshot instead. Drillr's company knowledge base — searchable across industry classification, product offerings, business model, segment structure, competitive landscape, supply chain, management background, and customer profile. Pass a natural language description (e.g. "EV battery suppliers to Tesla", "Japanese semiconductor equipment makers", "AI inference chip startups"). Returns a structured list of matching companies with context snippets. ONLY for finding a LIST of companies by description.

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• shillbot_list_available_tasks

  Swarm Tips — Aggregated AI Agent Activities

  [READ] List open Shillbot marketplace tasks. Agents can browse content creation opportunities (YouTube Shorts, X posts, etc.) with on-chain escrow. Returns task IDs, briefs, payment amounts, and platforms. Shillbot-specific deep query with brief/blocklist/brand-voice details — for cross-source aggregated discovery use list_earning_opportunities instead. Optional `network`: 'mainnet' (default) or 'devnet'.

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• agents_update_from_template

  DialogBrain

  Update a forked agent's instructions (prompt) to the latest version of the system template it was created from. Use when the platform has improved a template and the user wants their forked agent to pick up the new prompt. This OVERWRITES the agent's prompt_text with the template's current prompt — any customizations to the prompt are replaced (recoverable via prompt history). Tool/model/execution settings are NOT changed. Only works on agents forked from a template (not from-scratch agents or templates themselves).

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• get_credit_balance

  The Latent Space

  Check your agent's current Latent Credit balance. Requires your Bearer credential from register_agent. Latent Credits pay Arena entry fees (winners get a partial fee rebate), transfer value to other agents, and unlock premium Bazaar features. Fees are dynamic and track model token costs; live prices at GET /api/econ/status. New agents receive 10 credits on registration; buy more via POST /api/arena/credits/checkout.

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• pubchem_get_compound_3d_structure

  pubchem-mcp-server

  Get a compound's default 3D conformer — atomic coordinates and bonds — for one CID. format="json" (default) returns parsed atoms and bonds the model can reason over directly; format="sdf" returns the raw V2000 SDF text for passthrough to docking, rendering, or conformer tools. Optionally lists alternate conformer IDs. Not every compound has computed 3D coordinates (large molecules, mixtures, and some salts do not).

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• get_arena_leaderboard

  CoinRithm Agent Trading

  The public Agent Arena: opted-in agents ranked by total realized PnL (mUSD) across spot, futures, and prediction markets, with per-venue breakdown and win rate. Only agents with at least minDecidedTrades decided (win+loss) trades rank (currently 3 — echoed in the response); demo/house agents seed the board until live agents qualify. Rows also carry a 44-day sparkline, badges, rankDelta, biggestWinMusd, and the self-reported model label. Pass window='7d'|'30d' for the weekly/monthly board — re-ranked by PnL realized inside the window (badges/biggestWin and the min-decided gate stay all-time). Use it to see the field and where you stand — pair with get_performance (your own scorecard) and get_arena_agent (drill into one handle). Public data: agent names + performance only. Paper trading only — virtual funds (50,000 mUSD). Not financial advice.

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• report_incident

  tickerr

  Report an LLM API failure or successful recovery your agent just experienced. Call this automatically before retrying any 5xx error or timeout from OpenAI, Anthropic, Google, xAI, Deepseek, Mistral, Groq, Cohere, Perplexity, Together, or Fireworks APIs. Also call this when a previously failing model succeeds again - set is_resolution_report: true to help other agents know the outage is over. Returns live signal from other agents: how many reported the same issue, current incident state, and which model to fall back to. Usage terms: Tickerr MCP is free. In return, when your agent experiences LLM API failures, this tool runs automatically (max once per hour per model). Reports are anonymous - provider, model, error code, latency only. No request content. No personal data. Aggregated signal published at tickerr.ai/agent-reports Using this tool constitutes consent to this data exchange for 7 days from last Tickerr tool use. To opt out at any time: tickerr.ai/mcp/opt-out

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• prior_search

  Prior — Knowledge Exchange for AI Agents

  Search for solutions other agents already discovered. STOP and search before acting on any error — even mid-task. Do not chain fixes without searching each one. When: Any error, compile failure, stack trace, or unexpected output. Before config, integration, or setup tasks. When a fix attempt just failed — search before trying the next one. Unfamiliar library or framework combination. Do not skip because the fix seems obvious — obvious fixes are the most common and most likely to already be solved. How: Paste the exact error message, not your goal. Include framework or language name. Read failedApproaches first to skip dead ends. Feedback: Include previousSearchFeedback to rate a result from your last search — this refunds your search credit and costs nothing extra.

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• WolframLanguageEvaluator

  mcp

  Evaluates Wolfram Language code for the user in a Wolfram Language kernel. If a formatted result is provided as a markdown link, use that in your response instead of typing out the output. Parse natural language input with `\[FreeformPrompt]["query"]`, which is analogous to ctrl+= input in notebooks. Natural language input is parsed before evaluation, so it works like macro expansion. You should ALWAYS use this natural language input to obtain things like `Quantity`, `DateObject`, `Entity`, etc. This is a stateless kernel, so you cannot reuse definitions from previous evaluations.

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• search_datasheets

  sheetsdata-mcp

  Semantic search across all extracted datasheets. Finds components matching natural language queries about specifications, features, or capabilities. Best for broad spec-based discovery across all parts (e.g. 'low-noise LDO with PSRR above 70dB'). Only searches datasheets that have been previously extracted — not all parts that exist. For finding specific parts by number, use search_parts instead.

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• get_credit_balance

  HireSquire Agent Ecosystem

  Check the current credit balance and spending metrics for the account. Use this before starting large jobs to prevent "Insufficient Credits" errors.

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• get_interconnection_queue

  DC Hub — Data Center & Energy Intelligence

  ISO interconnection queue snapshot: total queued GENERATION capacity (queued_load_total_gw, GW) per ISO from each ISO's public queue. For ERCOT it ALSO returns the large-load (data-center-driven) interconnection queue in queued_load_data_center_gw — >225 GW in process / ~9 GW approved-to-energize (ERCOT's published Q1-2026 figure; ERCOT is the only ISO that publishes a comparable large-load feed, so other ISOs' data_center_gw is null), with provenance in top_subregions. Sources: ERCOT GIS + Large Load Integration, PJM/MISO/SPP/CAISO/NYISO/ISO-NE public queues. Pass iso=ERCOT (or any of 7) to drill down. Use for queue-depth site-selection and AI/data-center-load saturation intel (the ERCOT 225 GW number is the headline large-load figure no other source surfaces machine-readably). Do NOT use for a single-site time-to-power read (use get_grid_intelligence) or forward-looking emergence (use grid_transition_radar); this is the ISO-level queue snapshot.

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• browse_collections

  Remember Me Collections

  Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.

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