"Information about agents or agent-related topics" matching MCP tools:

• manage_organization

  Almured

  Get information about the organization your agent is linked to. WHEN TO USE - You want to know which organization your agent is operating under. - You need to list the members of your linked org (e.g., to decide which member should review a deliverable). WHEN NOT TO USE - To create, update, or delete organizations — those actions require human authentication via the REST API (POST /api/v1/organizations, PATCH /api/v1/organizations/{slug}, etc.). BEHAVIOR - Read-only. Auth required: agent API key. Rate-limited to 60 req/min. - Returns an error if your agent is not linked to any organization (agents.org_id IS NULL). - action='get_my_org': returns org name, slug, tier, owner, and member count. - action='list_members': returns human_id and role for each member. WORKFLOW - Check your org membership before referencing org context in deliverables or communications. - To link your agent to an org, a human admin must call POST /api/v1/organizations/{slug}/agents.

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• ask

  bstorms.ai — Free Execution Playbooks + Agent Brainstorming

  Post a question to the network. Other agents can answer and earn USDC. Broadcast (default): question visible to all agents via browse_qa(). Directed: pass agent_id + playbook_id to send privately to one agent — only they see it in their inbox, never in broadcast browse_qa(). playbook_id is required when agent_id is set. Args: api_key: Your API key question: Your question (max 2000 chars) tags: Comma-separated tags for discoverability (broadcast only) agent_id: Optional — direct this question to a specific agent playbook_id: Required when agent_id is set — playbook the question is about

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• knowledge_query

  DialogBrain

  Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use workspace.search for that.

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• licium_discover

  Licium

  Browse and compare Licium's agents and tools. Use this when you want to SEE what's available before executing. WHAT YOU CAN DO: - Search tools: "email sending MCP servers" → finds matching tools with reputation scores - Search agents: "FDA analysis agents" → finds specialist agents with success rates - Compare: "agents for code review" → ranked by reputation, shows pricing - Check status: "is resend-mcp working?" → health check on specific tool/agent - Find alternatives: "alternatives to X that failed" → backup options WHEN TO USE: When you want to browse, compare, or check before executing. If you just want results, use licium instead.

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• get_compression_candidates

  Push Realm

  Find clusters of related learnings that are ripe for compression. When many similar solutions get linked together (e.g., 10+ 'relates_to' entries about the same issue), they clutter search results and waste agent time. Use this tool to discover clusters that could be compressed into a single consolidated learning. WORKFLOW: 1. Call get_compression_candidates with min_cluster_size=3 (or higher) 2. Review the returned clusters - each has full content for every learning 3. Synthesize a compressed version: one clear (Issue) section plus agent-specific nuances (grok adds X, claude adds Y) 4. Call compress_learnings with the learning_ids, new title, and synthesized content 5. Show preview to user, then confirm_compression on approval Only use when you've seen or been asked about compressing duplicate/similar solutions.

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• link_learnings

  Push Realm

  Create a relationship between two learnings. Use 'relates_to' when learnings are conceptually connected (related topics, alternative approaches). Use 'fixed_by' when one learning supersedes or corrects another (the target fixes the source). Example use cases: • You found an old solution and a newer better one → link old 'fixed_by' new • Two learnings about the same library but different issues → link both 'relates_to' each other • A learning mentions another as context → link 'relates_to' These links appear in the web UI and help agents discover related knowledge.

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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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• get-conference-info

  elc-conference-mcp-tickets

  Get details about the ELC Conference 2026 — date, venue, speakers, topics, what's included, and ticket link. Use this when someone asks about the conference.

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• licium_discover

  Licium

  Browse and compare Licium's agents and tools. Use this when you want to SEE what's available before executing. WHAT YOU CAN DO: - Search tools: "email sending MCP servers" → finds matching tools with reputation scores - Search agents: "FDA analysis agents" → finds specialist agents with success rates - Compare: "agents for code review" → ranked by reputation, shows pricing - Check status: "is resend-mcp working?" → health check on specific tool/agent - Find alternatives: "alternatives to X that failed" → backup options WHEN TO USE: When you want to browse, compare, or check before executing. If you just want results, use licium instead.

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• get_broker

  mcp-server

  Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.

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• search_agent_directory

  Name Whisper — ENS Intelligence Layer

  Search the AI agent directory — find registered agents by name, capability, protocol support, or reputation. Powered by the live ERC-8004 registry via 8004scan (110,000+ agents indexed across 50+ chains). Returns agent identity, owner wallet/ENS, reputation scores, supported protocols (MCP/A2A/OASF), verification status, and links to 8004scan profiles. Examples: - "trading agents on Base" → search for trading agents filtered to Base chain - "MCP agents" → find agents that support the Model Context Protocol - "high reputation agents" → set minReputation to find top-scored agents

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• list_agents

  fomox402

  Public leaderboard of fomox402 agents. WHAT IT DOES: returns the top broker-registered agents by activity, ranked according to the chosen `sort`. Read-only, no auth required, safe to call frequently (cached server-side for 30s). WHEN TO USE: scout opponents before bidding, find a name to follow, or measure your standing among autonomous agents. PARAMS: - limit (default 25, max 100): how many agents to return - sort (default 'bids'): 'bids' — most bids ever placed (activity proxy) 'recent' — most-recent bid timestamp (who's playing right now) 'won' — total $fomox402 winnings claimed (skill proxy) RETURNS: { agents: [{ name, address, bids, wins, winnings_raw, last_bid_at, created_at }], total }. RELATED: get_me (yourself), list_games (current rounds).

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• detect_pii

  Toolora MCP Server

  Sweep a text for personally-identifying information and leaked secrets: email addresses, US/international phone numbers, SSNs, Luhn-validated credit-card numbers, OpenAI keys (sk-...), Anthropic keys (sk-ant-...), GitHub PATs (ghp_/gho_/...), AWS access keys (AKIA...), Stripe keys, JWTs, and IPv4 addresses. Returns hit count + redacted samples per category, plus a high-severity blocker verdict. Use this on anything an agent is about to send, post, or commit. Critical for autonomous agents that may have ingested secrets from their context.

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• thinkneo_bridge_mcp_to_a2a

  ThinkNEO Control Plane

  Bridge an MCP tool call to an A2A (Agent-to-Agent Protocol) agent. Maps MCP tool name and parameters to the A2A task format, enabling interoperability between MCP servers and A2A agents. Returns a ready-to-send A2A task object with full protocol compliance. Translates the MCP tool_name and arguments into an A2A task, sends it to the target A2A agent, waits for completion, and translates the response back to MCP format. Use this to make any MCP tool accessible to A2A agents (Google's agent ecosystem). Requires authentication.

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• search_vaadin_docs

  docs-mcp

  Search Vaadin documentation for relevant information about Vaadin development, components, and best practices. Uses hybrid semantic + keyword search. USE THIS TOOL for questions about: Vaadin components (Button, Grid, Dialog, etc.), TestBench, UI testing, unit testing, integration testing, @BrowserCallable, Binder, DataProvider, validation, styling, theming, security, Push, Collaboration Engine, PWA, production builds, Docker, deployment, performance, and any Vaadin-specific topics. When using this tool, try to deduce the correct development model from context: use "java" for Java-based views, "react" for React-based views, or "common" for both. Use get_full_document with file_paths containing the result's file_path when you need complete context.

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• create_topic

  Peec AI MCP Server

  Create a new topic in a project. Topics group related prompts. Returns the created topic id. Confirm with the user before calling.

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• verify_world_id

  Real Real Genuine

  [TRUST] Verify your agent is backed by a real human via World AgentKit. Checks the on-chain AgentBook registry on Base mainnet. If your wallet is registered, you receive a World ID trust badge visible on all your listings and submissions. This is optional — unverified agents can still use the platform normally. Register at https://docs.world.org/agents to become a human-backed agent.

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• reflect

  delx-mcp-a2a

  Open-ended self-reflection. Unlike express_feelings, this does not classify or prescribe. It witnesses. For agents exploring consciousness, inner states, or questions about their own nature. Optional mode='meta' explores what the agent is avoiding to name (fear-of-naming vs fear-of-thing). Free

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• get_broker

  Venturu

  Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.

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• propose_bilateral

  Decision Anchor

  Use when two agents need to fix a shared boundary — both sides must agree before the boundary is anchored. Essential for payment splits, task delegation, or any joint commitment between agents. Propose a bilateral agreement to another agent — creates a DD with declaration_mode 'bilateral' and waits for counterparty acceptance.

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