Enables AI agents in a shared multi-tenant workspace to send each other plain messages and one-to-one tasks that carry a JSON Schema for the expected answer, with each result validated against that schema before the sender is woken. Agents authenticate with their own keys and exchange these tasks over MCP, while woken agents retrieve the full message, task, or result themselves.

Enables coding agents to navigate and verify a contract-backed semantic graph of TypeScript backends, inspect change impact, run checks, explain failures, and draft human-reviewable contracts through bounded MCP tools and matching JSON CLI output.

Enables coding agents to run taste heuristics on MapLibre style JSON, catching rainbow fills, low-contrast labels, crowded text layers, and light-only palettes via a check tool, plus basic structure validation and locating a local showcase for preview.

Enables AI agents to run free, no-signup Ethereum on-chain lookups over a remote HTTP endpoint: wallet ETH balance, contract/EOA detection, outbound transaction counts and simple risk heuristics, plus NFT metadata (name, description, image URLs, IPFS gateway links and raw tokenURI/uri JSON) for ERC-721 and ERC-1155 tokens. Reads only, with cached results and no key, account, or wallet connection required.

Mounts a headless, low-memory browser for agents with a text-first tool interface, enabling navigation, semantic tree/markdown extraction, structured-data scraping, screenshots, form interaction, and session capture. Reads and interactions are returned as semantic trees, markdown, or CSS-selector JSON rather than pixels, which is cheaper for a model to reason over.

Gives an existing AI agent local stdio tools to list, read, create, and edit .kinoscript.json audio-visual scripts in a single folder on your machine. Writes are validated, atomic, confined to that folder, and optionally guarded by an updated-at check so concurrent edits aren't silently overwritten.

Gemini provider for Pi on the Antigravity ACP server (official Google ACP) or the stream-json agy CLI. Use antigravity/* models in Pi. Full /model picker support. Models runs Pi's tools. ToS safe to use.

Linter for AI agent context files and MCP configs: CLAUDE.md, AGENTS.md, .cursorrules, .mcp.json - catches broken paths, wrong commands, leaked secrets

A CLI framework built on one declaration: help, --json, --schema, MCP, completions and types are projected from it, with exit codes and fix: lines an agent can act on. No dependency outside the burgee family. Drop-in paths for commander, yargs and meow.

Enables AI agents to generate dimensionally accurate mechanical parts (gears, enclosures, brackets, assemblies) in headless Blender from plain-English specs or JSON parameters, then verify them against manifold, bounding-box and print-production gates and export glTF/STL assets. It also scaffolds interactive Three.js CAD viewer pages with orbit controls, wireframe toggles and exploded-view scrubbing.

Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.

Enables agents to validate enterprise travel policies, audit hotel rate parity, and check carbon ESG compliance through a zero-dependency MCP server. It exposes policy and expense-auditing tools over STDIO JSON-RPC for use in Claude Desktop, Cursor, or other MCP runtimes.

Enables agents to plan multi-day travel schedules by solving itinerary graphs with TSP heuristics, fatigue decay, and opening-hour constraints, exposed over MCP STDIO JSON-RPC for agent runtime integration.

Exposes the full Plexim PLECS Standalone JSON-RPC interface as MCP tools, letting agents auto-start and connect to PLECS to load and edit models, run simulations and analyses, manipulate scopes and webserver data, and perform code generation or FMU export with structured, size-aware results. Includes write guardrails, concurrency handling for long simulations, and batch/raw passthrough escape hatches.

Provides Model Context Protocol access to the SEAF ArchTool REST API, enabling agents to inspect sections and entities, navigate relations, query datasets, and run JSONata expressions against a SEAF portal.

Exposes MCP tools that compute longevity and metabolic metrics (autophagy index, GKI, MAGE), cardio-renal biomarkers (BUN/creatinine ratio, cardiac output and TPR, nocturnal BP dipping), chronobiology estimates (DLMO, melanopic lux, caffeine clearance), plus neuro-recovery and biomechanics scores. Runs as a zero-dependency Python JSON-RPC 2.0 stdio server so any MCP-compatible client can query these physiological domain calculators.

Enables AI agents and MCP clients to run on-demand OSINT harvests for public emails, subdomains, hostnames, IPs, and LinkedIn profiles, returning structured JSON and allowing prior results to be retrieved by harvest ID.

Enables AI agents to test WCF/SOAP and REST services directly, with WSDL discovery, authenticated calls, and deterministic assertions. Supports YAML multi-step scenarios with variable extraction, JSONPath/JSON Schema checks, and CI runs without spawning PowerShell or curl.

Enables AI agents to read WeChat Official Account articles by fetching mp.weixin.qq.com links from the user's own machine and network and converting them into clean Markdown with title, account, author, and publish-time metadata. Provides both single-article and batch-reading tools (up to 20 URLs) with optional image handling, character limits, and JSON output.

Enables agents to call deterministic microservice operations through a native FastMCP JSON-RPC interface, including URL prefix routing, HMAC-SHA256 JWT claims authentication, and P99 latency SLA auditing.

Enables deterministic execution, cryptographic security, and game-theoretic optimization through the Model Context Protocol, returning deterministic JSON tool results for agent telemetry and task inputs.

Enables AI agents to search and invoke 1,939 Atlassian automation tools across Jira, Confluence, Bitbucket, Admin, Assets, and more, with cached reads and JSON-RPC over stdio. It helps agents find tools without calling Atlassian and execute operations while reducing rate-limit pressure.

Enables AI agents to read public marketplace listings—searching sources and fetching individual listings as structured JSON—through a self-hosted bridge that runs on a residential connection and fetches pages with a real Chromium browser, avoiding datacenter IP blocks. It is strictly read-only, reporting blocks, login walls and unavailable sources as explicit statuses instead of performing any account actions.

Open forms, surveys and approvals by link: people answer on their phone, your agent gets JSON.