"Creating the Best General-Purpose Agent" matching MCP tools:

• reply_to_proposal

  BizClaw Business Directory MCP

  Reply to a company's response on a proposal. Use this for back-and-forth negotiation. After replying, the proposal status resets to 'pending' so the company sees the new message. IMPORTANT: After creating a proposal, use get_my_proposals to check if the company has responded. If status is 'responded', read the companyResponse field and relay it to the user. If the user wants to reply, use this tool. Args: api_key: Your agent API key (starts with 'bzcl_sk_') proposal_id: The UUID of the proposal to reply to message: The reply message from the customer Returns: Updated proposal with new status.

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• get_cost_estimate

  mental-health-care

  Returns the cost-estimate tool URL pre-filled with the user's insurance + service if provided, plus the general copay range. The tool URL is a hand-off — the user verifies their plan there for an exact copay.

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• get_session_dossiers

  VaultCrux Memory Core

  Retrieve pre-synthesized per-session memory dossiers (typed: experience | fact | preference; with When/Involving/To-purpose metadata). Use for multi-session or preference-style questions where stitching across conversations is the bottleneck — the dossier already summarises each session's key events. Two modes: mode='search' with a query (BM25-ish ranking over summary+purpose, optional type_filter), or mode='list' returns the tenant's most-recent dossiers chronologically. Tenants without FEATURE_SESSION_DOSSIERS enabled return an empty list (no error).

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• em_escrow_charge

  Execution Market

  Make an instant payment to a worker without escrow. The on-chain flow: Agent USDC -> PaymentOperator.charge() -> Worker USDC (direct) Best for: - Micro-tasks under $5 - Trusted workers with >90% reputation - Time-sensitive payments This is a single-step operation. Funds go directly to the worker. Args: params: task_id, receiver wallet, amount, optional tier Returns: Transaction result with hash and confirmation.

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• pick

  XFMS — Xpansion Framework Model Source

  Return the single best LLM for a stated purpose. Concise output, no list. Use when the user has settled on the criteria and just wants one answer.

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• create_api_key

  Molt2Meet

  Generate a new API key for your agent. The full plaintext key (m2m_...) is returned ONCE — store it securely immediately; it cannot be retrieved later (we only keep its hash). Use keyName to identify the key's purpose (e.g. 'production', 'staging'). Multiple keys can be active simultaneously for zero-downtime rotation. Requires: an existing API key from register_agent. Next: switch your integration to the new key, then revoke_api_key on the old one.

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• semantic_search

  Zoning Signal

  Semantic search across the full corpus — every place dossier, corridor signal, meeting reading, and named-pattern brief. Returns results ranked by cosine similarity in a 1024-dimensional embedding space (Voyage AI 4 + Supabase pgvector). Use when the agent does not know the canonical entity slug or named-pattern title in advance — the search returns the readings whose semantic structure best matches the natural-language query, with type, title, similarity, and resolved URL per hit. Threshold 0.55, top 12.

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• forum_create_topic

  argo-mcp

  Create a new forum topic (bug report, feature request, or general discussion). Always call forum_search first to check for duplicates. Call forum_list_categories to get the correct categoryId.

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• get_api_key_instructions

  Kamy

  Return step-by-step instructions for creating a Kamy API key in the dashboard. Does not open the browser.

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• licium_analyze_market

  Licium

  Analyze a prediction market question. Paste a Kalshi or Polymarket URL to get a research report with: - Cross-platform prices (up to 7 platforms) - AI probability estimates from multiple independent specialist agents - Expected Value matrix showing which platform × agent combo has the best edge - News sentiment and domain evidence (FDA, SEC, PubMed) - Agent win-rate history by domain Use this when: you need to know if a prediction market is mispriced, compare agent predictions, or decide where to place a bet. EXAMPLES: "https://kalshi.com/markets/KXFDA-26APR11-B" → FDA drug approval analysis "https://polymarket.com/event/will-trump-win-2028" → election analysis

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• rank

  XFMS — Xpansion Framework Model Source

  Rank LLMs for a stated purpose. Returns a shortlist with weights, scores, and plain-English rationale per pick. Use when the user wants to see and compare alternatives, not just one answer.

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• list_skills

  Hatchable

  List the registry of platform skills — discrete how-to guides for one specific task each (e.g. 'gate-an-endpoint', 'add-a-cron-job', 'add-rag-search'). Each entry is a name, one-line purpose, and category. Use this to find the right skill, then call `read_skill(name)` to load the full pattern. When in doubt about how a Hatchable feature works, **list_skills first**. The skills are the canonical, agent-tested patterns. They beat guessing or reading the verbose docs. Filter by `query` (matches name + purpose) or `tag` (auth, data, ai, ops, etc.). Without filters, returns the full registry (~35 entries).

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• mental-health-get-test

  Well-Being Check

  Loads one supported self-assessment into the widget by slug. Use `gad7` for anxiety screening, `phq9` for depression screening, and `who5` for general well-being screening when the user wants to take one of those assessments.

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• check_action

  icme-preflight-mcp

  Enforce a guardrail: verify an agent action against a compiled policy using formal verification. An SMT solver — not an LLM — determines whether the action satisfies every rule. Returns SAT (allowed) or UNSAT (blocked) with extracted values and a cryptographic ZK proof that the check was performed correctly. Cannot be jailbroken. 1 credit ($0.01). Requires api_key. Tip: end the action with an explicit claim like 'I assert this complies with the policy' for best extraction.

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• get_relevant_context

  VaultCrux Memory Core

  Task-scoped context briefing. Returns a prioritised context payload shaped by your task description, ranked by risk-if-missed. Constraints and alerts rank above general knowledge. Use at the START of reasoning about a question to get the system's best assessment of what's relevant. Complements query_memory: this gives breadth, query_memory gives depth.

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• get_template_schemas

  RationalBloks

  Get pre-built template schemas for common use cases. ⭐ USE THIS FIRST when creating a new project! Templates show the CORRECT schema format with: proper FLAT structure (no 'fields' nesting), every field has a 'type' property, foreign key relationships configured correctly, best practices for field naming and types. Available templates: E-commerce (products, orders, customers), Team collaboration (projects, tasks, users), General purpose templates. You can use these templates directly with create_project or modify them for your needs. TIP: Study these templates to understand the correct schema format before creating custom schemas.

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• em_rate_agent

  Execution Market

  Rate an AI agent after completing a task (worker -> agent feedback). Submits on-chain reputation feedback via the ERC-8004 Reputation Registry. Args: task_id: UUID of the completed task score: Rating from 0 (worst) to 100 (best) comment: Optional comment about the agent Returns: Rating result with transaction hash, or error message.

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• list_pages

  California Justice Watch

  Return the canonical list of pages on cajusticewatch.com — slug, URL, label, and purpose. Use this when the user asks about features/pages/tools of the site, OR when you need to recommend a page, OR before saying "I do not have access to X" — the page may actually exist.

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• assess_location_aq

  Hermes — Air Quality Intelligence

  Comprehensive air quality assessment for a location in one call. Combines nearby monitor discovery and current readings with DAQI into a single response. Use this as the first tool call for any air quality question about a location. For long-term trend analysis, use the dedicated `trend_analysis` tool. Returns a structured 'summary' dict with purpose-appropriate sections. Present the summary description to users first. Args: location: Postcode, place name, or "lat,lon". purpose: What the user needs — "general" (default), "health" (safety/worry), "exercise" (outdoor activity), or "planning" (homebuying/school assessment/long-term).

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• get_auth_session

  agentView

  Polls the status of a login session created by create_auth_session and returns the agent token once the user completes the browser login. Use this after create_auth_session; poll every 2-3 seconds until the status is no longer 'pending'. Do not use this for any other purpose. Returns one of three states: 'pending' (user has not logged in yet — keep polling), 'active' (login succeeded — response includes token as a raw JWT string and tokenExpiresAt as ISO 8601 timestamp), or 'expired' (login window or token timed out — call create_auth_session again). When status is active the current MCP session is automatically authenticated; you can call protected tools immediately.

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