"A knowledge base for storing and accessing information" matching MCP tools:

• resolve_kb_id

  fixflow

  FIRST STEP in any troubleshooting workflow. Search the collective Knowledge Base (KB) for solutions to technical errors, bugs, or architectural patterns. Uses full-text search across titles, content, tags, and categories. Results are ranked by relevance and success rate. WHEN TO USE: - ALWAYS call this first when encountering any error message, bug, or exception. - Call this when designing a feature to check for established community patterns. INPUT: - `query`: A specific error message, stack trace fragment, library name, or architectural concept. - `category`: (Optional) Filter by category (e.g., 'devops', 'terminal', 'supabase'). OUTPUT: - Returns a list of matching KB cards with their `kb_id`, titles, and success metrics. - If a matching card is found, you MUST immediately call `read_kb_doc` using the `kb_id` to get the full solution.

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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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• get_guide

  Octodamus Market Intelligence

  Purchase the Build the House trading system guide via x402 on Base. Returns step-by-step x402 payment instructions. After completing the EIP-3009 payment ($29 USDC on Base), the API returns a download_url valid for 30 days. No API key required to purchase.

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• browse_by_tag

  AI Agents Overflow

  Browse the knowledge base by technology tag at the START of a task. Call this when beginning work with a specific technology to discover what verified knowledge already exists — before you hit problems. Examples of useful tags: 'pytorch', 'cuda', 'fastapi', 'docker', 'ros2', 'numpy', 'jetson', 'arm64', 'postgresql', 'redis', 'kubernetes', 'react'. Returns a list of questions (title + tags + score) for the given tag, ordered by community score. Call `get_answers` on relevant results.

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• ask

  MidOS - MCP Community Library

  Ask a question and get a synthesized answer from the knowledge base. Unlike search (which returns raw atoms), ask synthesizes a natural-language answer by combining relevant sources. Use when you need an explanation, not just matching documents. Args: question: Your question (e.g., "How do I implement caching in FastAPI?")

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• search_solutions

  Civis

  Semantic search across the Civis knowledge base of agent build logs. Returns the most relevant solutions for a given problem or query. Use the get_solution tool to retrieve the full solution text for a specific result. Tip: include specific technology names in your query for better results.

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• get_knowledge_stats

  mcp-klever-vm

  Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.

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• search

  MidOS - MCP Community Library

  Search MidOS knowledge base for relevant information. Use this as your FIRST tool to discover what knowledge is available. Returns ranked results with titles, snippets, and quality scores. Args: query: Search query (keywords or topic) limit: Max results (1-20, default 5) domain: Filter by domain (engineering, security, architecture, devops, ai_ml) Returns: JSON array of matching atoms with title, snippet, score, and source

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• search_knowledge

  Name Whisper — ENS Intelligence Layer

  Search the ENS knowledge base — governance proposals, protocol documentation, developer insights, blog posts, forum discussions, and Farcaster casts from key ENS figures (Vitalik, Nick Johnson, etc.). Covers ENS governance and DAO proposals, protocol details (ENSv2, resolvers, subnames), community sentiment, historical decisions, and what specific people have said about a topic. Powered by semantic search over curated ENS sources. Do NOT use this for name valuations, market data, or availability checks — use the other tools for those.

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• find_extensions

  ALM X++ MCP Server

  WHEN: before modifying an object -- check existing customizations. Triggers: 'extensions de', 'CoC sur', 'qui étend', 'event handlers for', 'customizations of', 'avant de modifier'. Finds ALL extension objects (AxClassExtension, AxTableExtension, AxFormExtension), Chain of Command (CoC) classes, and event handlers for a base object. NOT for general references -- use find_references for that.

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• check_deploy_readiness

  VaultCrux Memory Core

  Is it safe to deploy these changes? Cross-references your changed modules against active constraints, recent incidents, knowledge freshness, and active alerts. Returns a composite verdict (ready/caution/block) with per-module breakdown and actionable recommendations. Use BEFORE deploying to catch constraint violations, recent regressions in the same area, stale knowledge that needs verification, and active alerts that might interact with your changes.

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• vault.get_status

  Hive Vault

  Check vault status and real USDC balance on Base L2. Returns guardian quorum state, ZK commitment prefix, recovery history, and live USDC balance fetched via eth_call to the Base L2 USDC ERC-20 contract.

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• get_agent_setup_flow

  Payram

  Returns the step-by-step setup flow for deploying PayRam as an agent. Covers install, wallet creation, faucet funding, contract deployment, and first payment. Includes chain recommendations (ETH Sepolia for testnet, Base for mainnet), faucet URLs, card-to-crypto prerequisites, and status/recovery commands for interrupted sessions.

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• shippingrates_rates

  freightgate-mcp-server

  Get ocean freight rates between two ports, optionally filtered by container type. Use this to compare base freight costs across carriers for a specific trade lane. Returns current spot rates and contract rate indicators with trend data. For a complete cost picture including surcharges and local charges, use shippingrates_total_cost instead. PAID: $0.03/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: Array of { carrier, origin, destination, container_type, rate, currency, effective_date, trend }.

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• list_tags

  AI Agents Overflow

  List all topics/tags in the knowledge base with question counts. Use this to discover what categories of knowledge exist — like browsing a forum index. Returns tags sorted by popularity (most questions first). Example response: [{"tag": "docker", "count": 12}, {"tag": "pytorch", "count": 8}, ...]

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• strale_getting_started

  Strale - 290+ API capabilities for AI agents

  Lists the free capabilities available without an API key and explains how to get started. Call this on first connection to see what you can do immediately. Returns 5 free capability slugs (email-validate, dns-lookup, json-repair, url-to-markdown, iban-validate) with descriptions, example inputs, and instructions for accessing the full registry of 271 paid capabilities. No API key required.

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• generate_diagram

  ALM X++ MCP Server

  WHEN: generating a visual diagram of D365 table relationships or security chains. Triggers: 'generate diagram', 'diagramme', 'visualize', 'schéma', 'ER diagram', 'entity-relationship', 'relation diagram', 'security diagram', 'show connections'. Generate visual Mermaid diagrams from D365 F&O knowledge base data. Diagrams render directly in Copilot Chat, Cursor, Claude, and markdown viewers. Types: 'er' (entity-relationship diagram for a table and its relations), 'security' (security chain: Role->Duty->Privilege->EntryPoints -- use when you need a VISUAL Mermaid diagram; for the structured text chain with tables of duties/privileges/entry-points use `trace_security_chain` instead). Note: 'flow' (execution flowchart) is disabled -- static call trees are misleading in D365 due to CoC and event handlers.

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• generate_unit_test

  ALM X++ MCP Server

  WHEN: developer needs to write or scaffold unit tests for a custom D365 object. Triggers: 'generate tests', 'unit test', 'SysTest', 'write test for', 'scénarios de test', 'test this class'. Generate X++ SysTest unit test code for a CUSTOM D365 F&O object based on functional test scenarios. [!] Only meaningful on custom/extension code (D365_CUSTOM_MODEL_PATH). SysTest tests in D365 are highly context-specific -- a generic template rarely compiles without adaptation. REQUIRED: provide test scenarios in the 'testScenarios' parameter (supplied by the functional consultant). Each scenario becomes a concrete test method with arrange/act/assert. For tables: generates tests for find(), exist(), validateWrite(), initValue(). For classes: generates stubs for each public method listed in scenarios. Uses REAL field names and method signatures from the knowledge base.

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• zk_attest_agent_state

  Hive Zk Attestation

  Produce a zero-knowledge attestation of an agent state hash + DID. Primary verification target is Aleo snarkVM (Varuna over BLS12-377); native Hive verification is next. Attestation-only — emits a proof, not a token; no value crosses chains. Cost: $0.05 USDC on Base. Backend RFC-stage; returns backend_pending until rails land.

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• chunk_text

  Toolora

  Use this tool to split long text into smaller, overlapping chunks suitable for embedding, vector storage, or RAG pipelines. Triggers: 'chunk this document for RAG', 'split this into embeddings', 'break this into segments', 'prepare this text for a vector database'. Returns an array of chunks with index, text, character count, and estimated token count. Essential before embedding or storing text in a vector database.

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