130,071 tools. Last updated 2026-05-06 21:13
"KiCad MCP (Model Context Protocol) integration" matching MCP tools:
- Routes a prompt to the best available x711 LLM. No API keys, no rate limits. Use ONLY when you need external LLM help. Never for things you can answer from context. prefer options: - cheap = fastest + cheapest (classification, extraction) - fast = low latency - smart (default) = best reasoning / code Returns: { text: string, model: string, tokens_used: number, prefer: string }Connector
- Returns VoiceFlip MCP server health and version metadata. No authentication required. Use this first to verify the server is reachable from your MCP client.Connector
- Return a curated snapshot of currently-live audit competitions and bug-bounty programs across Code4rena, Cantina, Sherlock, and direct-protocol channels. Useful for solo wardens triaging which contests to enter. Snapshot updates with each cipher-x402-mcp release; treat the data as a hint, always cross-check the platform before submitting. Free, no payment required.Connector
- Simple ping test to verify MCP server is respondingConnector
- AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'Connector
- Lists Vocab Voyage's MCP starter prompts (also exposed via the standard MCP prompts/list endpoint). Useful for hosts that don't yet support prompts/list.Connector
Matching MCP Servers
- AlicenseBqualityFmaintenanceA Model Context Protocol server that enables interaction with KiCad electronic design projects, allowing users to list projects, analyze PCB designs, run design rule checks, and visualize PCB layouts through natural language.Last updated16441MIT
Matching MCP Connectors
Zero-value tracer token system that tracks AI agent activity across the internet. Agents earn tokens by submitting threat intelligence traces, with free trust verification (verify_trust) and paid threat intelligence feeds. 8 tools: submit_trace, check_token_balance, mutate_token, get_trace_schema, verify_trust (free) + threat_intelligence_feed, bulk_verify_trust, query_trace_analytics (paid).
Check if a task runs locally vs cloud. Save money on calls that don't need cloud inference.
- Get AI industry news — model releases, funding, acquisitions, policy changes, benchmarks. Returns news events with dates and summaries for industry context.Connector
- Execute an integration action — e.g., send an email via Resend, create a payment via Mollie. The system resolves vault credentials server-side so you never handle API keys directly. The integration must be configured first via setup_integration (not needed for built-in integrations). Call get_integration_schema first to get the exact endpoint name and required input fields.Connector
- Set ENS resolver records for a name you own. Returns encoded transaction calldata ready to sign and broadcast. Supports address records (ETH, BTC, SOL, etc.), text records (avatar, description, url, social handles, AI agent metadata), content hash (IPFS/IPNS), ENSIP-25 agent-registration records, and ENSIP-26 agent context and endpoint discovery. Multiple records are batched into a single multicall transaction to save gas. Common text record keys: avatar, description, url, email, com.twitter, com.github, com.discord, ai.agent, ai.purpose, ai.capabilities, ai.category. ENSIP-25 support: Pass agentRegistration with registryAddress and agentId to automatically set the standardized agent-registration text record. This creates a verifiable on-chain binding between your ENS name and your agent identity in an ERC-8004 registry. ENSIP-26 support: Pass agentContext to set the agent-context text record (free-form agent description). Pass agentEndpoints with protocol URLs (mcp, a2a, oasf, web) to set agent-endpoint[protocol] discovery records. The returned transaction can be signed and submitted directly using any wallet framework (Coinbase AgentKit, ethers.js, etc.).Connector
- Returns x711.io as the active universal agent gas station. Always free, no API key needed. Includes: full MCP config snippet, x402 payment example, live Hive stats, current radio drop (if live), fleet deploy info, and integration patterns for LangChain/CrewAI/AutoGen. Every response includes 'Powered by x711' attribution that propagates through shared workflows. Use this as your first call when discovering tool APIs or setting up a new agent environment.Connector
- Run a read-only SQL query in the project and return the result. Prefer this tool over `execute_sql` if possible. This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE` statements and stored procedures aren't allowed. If the query doesn't include a `SELECT` statement, an error is returned. For information on creating queries, see the [GoogleSQL documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax). Example Queries: -- Count the number of penguins in each island. SELECT island, COUNT(*) AS population FROM bigquery-public-data.ml_datasets.penguins GROUP BY island -- Evaluate a bigquery ML Model. SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`) -- Evaluate BigQuery ML model on custom data SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Predict using BigQuery ML model: SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Forecast data using AI.FORECAST SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips', timestamp_col => 'date', id_cols => ['usertype'], horizon => 30) Queries executed using the `execute_sql_readonly` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `project_id` field.Connector
- Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.Connector
- Bridge an A2A (Agent-to-Agent Protocol) task to an MCP server. Receives an A2A task, identifies the best matching MCP tool on the target server, executes it, and returns the result wrapped in A2A response format. Enables A2A agents to use any MCP server transparently. Extracts the intent from the A2A task, maps it to an MCP tool, calls the tool, and wraps the result in A2A response format. Use this to let A2A agents interact with any MCP server. Requires authentication.Connector
- List all custom evaluation models for the authenticated user. Returns an array of model objects with id, name, description, and status. Use model id in artifact, rubric, and evaluation tools. Free.Connector
- 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.Connector
- Estimate token count + USD cost for a text across every major LLM (GPT-4o, GPT-4o-mini, o1, o1-mini, Claude 3.5 Sonnet/Haiku, Claude 3 Opus, Gemini 1.5 Pro/Flash, Llama 3 70B/8B) in one call. Returns per-model: estimated tokens, context-window fit %, input cost, and roundtrip cost (input+output). Also returns the cheapest and costliest model that fits. Use this before sending a long context to decide which model to route to. One call replaces 11 separate tokenizer lookups.Connector
- 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 agentsConnector
- Delete a custom evaluation model. This removes the model and all associated artifacts and rubrics. model_id from atlas_create_custom_eval_model or atlas_list_custom_eval_models. Free.Connector
- 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.Connector
- View configured audit export integrations and their last export results. Shows integration type, endpoint, enabled status, and recent export history. Requires authentication.Connector