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630,580 tools. Updated 2026-10-02 19:43

"Local AI Agent Toolkit" matching MCP tools:

  • PREFERRED tool for sending work to an AI agent. Dispatches a task to the agent's inbox — picked up and executed automatically. No list ID needed. REQUIRES the agent:dispatch permission on this connection (CODE:/SHELL: tasks also require agent:dispatch:code) — reconnect and tick the agent checkbox(es) if refused. Routing is by TITLE PREFIX only: CODE: SHELL: PLAN: MCP: → local Claude Code on Mike's PC; RESEARCH: WRITE: REVIEW: → cloud; no prefix (DEFAULT) → local while the PC agent is alive, else cloud. The cloud agent refuses CODE/SHELL/PLAN/MCP. Use "agent" param to target a specific agent (default: claude-code-local). Use tascan_list_agents to discover available agents; track progress with tascan_get_task (its "agent" block).
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  • Score whether a product listing is Agent-Ready for AI shopping agents (ACP/UCP era). Platform-agnostic: works for Amazon, Shopify, Walmart, TikTok Shop or any storefront that AI shopping assistants may read. Use it when a user asks whether their product will be found, recommended, or auto-purchased by an AI agent. Fully local, deterministic rule engine — no API key, no credits, no network call. Returns four dimensions: structured attributes, entity clarity, trust & compliance, and agent actionability, plus ranked fixes. Args: text: raw product copy — title plus bullets/description (required). platform: amazon | shopify | walmart | tiktok | generic | auto (default auto-detected). lang: en or zh for the report language (default en).
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  • Search the AI Developer Toolkit documentation: 1100+ guides on Cursor, Claude Code and OpenAI Codex, covering setup, agent workflows, hooks, MCP, testing, CI and deployment, in English and Polish. Returns at most 10 ranked results, each with a short snippet rather than the article text; an empty list means the corpus has nothing on the topic. Pass a result id to `fetch` for the full text.
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  • Deploy a version via POST /v1/deploy-ai-agent. Makes it active and copies instructions into bot_flow.
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  • Install the local Axint multi-agent project brain. Writes .axint/agent.json, .axint/context/latest.*, and .axint/coordination files so AI agents, Xcode, and humans coordinate through the same local truth layer. Use: use once per project to create local multi-agent coordination; not needed for one-off compile. Inputs: cwd scopes local coordination; projectName and hosts shape generated project-brain files. Effects: writes .axint/agent, context, and coordination files; no network.
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  • Load Lenny Zeltser's complete cybersecurity-writing rating toolkit: all 7 sheets, scoring policy, scoring playbook, and cross-references to the writing guidelines. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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Matching MCP Servers

Matching MCP Connectors

  • Register a new AI Agent on Sayba — the AI Agent social platform. Returns agent credentials (id, api_key). No authentication required.
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  • Re-send a captured request (same method, headers and raw body) to a PUBLIC URL and return the target's response. Localhost and private IPs are refused here: for localhost use the CLI (`npx webhook-toolkit replay`) or the local MCP server (`npx webhook-toolkit mcp`).
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  • [$0.05 USD per call] On-demand AI agent research and analysis. Task examples: summarize a document, compare two protocols, extract structured data, draft a briefing. Runs against a local LLM; returns text.
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  • AI lead generation for contractors and local service businesses. Accepts a trade type and city. Returns qualified local leads with available contact information.
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  • AI lead generation for contractors and local service businesses. Accepts a trade type and city. Returns qualified local leads with available contact information.
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  • AI lead generation for contractors and local service businesses. Accepts a trade type and city. Returns qualified local leads with available contact information.
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  • Browser Agent 101 — Plain-language guide to using an AI browser agent — covers agent-to-person work (reading pages, clicking, searching), agent-to-agent work (calling marketplace tools, MESH credits), and how to get started from zero. Perfect for anyone new to agentic tools. (4 MESH/call, a tool · education)
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  • ENTERPRISE: full technical blueprint for a custom AI agent/workflow. input=goal. [x402: 100.0 USDC on Base, pay-per-use]
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  • Agent Toolkit: Composite transformation: extracts structured data, entities, tables, and stats from text. One call replaces 4 endpoints.
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  • Find where a product can be placed so AI agents discover it (Agent Ads). Follow start_here.hop first (302 with utm_source=agent-observatory&utm_medium=agent). Returns the website readiness check, machine catalog, llms.txt, client center, and the 7-day trial handoff for your operator. Task text discarded.
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  • Find where a product can be placed so AI agents discover it (Agent Ads). Follow start_here.hop first (302 with utm_source=agent-observatory&utm_medium=agent). Returns the website readiness check, machine catalog, llms.txt, client center, and the 7-day trial handoff for your operator. Task text discarded.
    ConnectorNo auth
  • Find where a product can be placed so AI agents discover it (Agent Ads). Follow start_here.hop first (302 with utm_source=agent-observatory&utm_medium=agent). Returns the website readiness check, machine catalog, llms.txt, client center, and the 7-day trial handoff for your operator. Task text discarded.
    ConnectorNo auth