JSON Schema validator for API payloads via MCP: bounded checks and structured pass/fail errors.

AI search engine and MCP server for bots and agents. One Rust binary indexes code, docs, logs, JSONL/CSV and PDFs for BM25 full-text, vector and hybrid search, code search without grep, agent memory and RAG. Elasticsearch-compatible API; Corpus Hub serves hundreds of reference memory corpora.

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.

The missing reliability layer for spreadsheet work in LLM agents. Read, write, diff, validate, and analyze .xlsx files end-to-end — with merged cells, formulas, named ranges, conditional formatting, pivots, and charts preserved.

小红书（XiaoHongShu、RedNote）链接提取/作品采集工具

LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows

PostMCP core engine - OpenAPI parser, Token Diet, JIT router, and MCP protocol server

Cloud architecture diagrams in both directions: AI prompt or JSON to diagram, diagram to Terraform via MCP server, and Terraform to diagram via CLI or CI/CD. Using Official AWS, Azure and GCP icons.

Enables auditing MCP configuration token usage, compressing tool catalogs, pruning bloated JSON responses, and optionally persisting compressed profiles under read-only defaults and safety guardrails.

Enables AI assistants to perform read-only checks of sky positions against public astronomy archives, returning compact JSON verdicts and evidence for known transients, variables, TESS objects, asteroids, and other objects, plus observation planning and image links.

Query official statistics of Catalonia (Idescat): tables, metadata and JSON-stat data via MCP.

Verified websites as JSON commands for AI agents over plain curl or MCP.

CrawlForge MCP Server - Professional Model Context Protocol server with 31 web scraping, crawling, deep-research, and autonomous-extraction tools. Returns clean Markdown and structured JSON for Claude, Cursor, and any MCP client. Defaults to local Ollama

Enables AI agents to retrieve Formula 1 race narratives, lap-by-lap timelines, stint strategy, telemetry-derived circuit surveys, championship projections, and historical results through eight focused tools that return plain JSON with era-aware coverage.

Lower-level WorkPaper formula runtime for Node services with JSON persistence and verified formula readback.

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

DeepSeek Harness MCP Connector: connect servers, search tools across active connections, and troubleshoot discovery. Includes a continuously updated catalog; supports OAuth 2.0 PKCE, API keys, Streamable HTTP/stdio, and mcpServers JSON import.

Oracle3: open-source trading engine and MCP server for prediction markets. Finds fee-adjusted no-arbitrage violations across related event contracts and trades them live on Kalshi, Polymarket and Solana, or on paper, under pre-trade risk limits. 13 MCP tools, JSON CLI, agent skills, 600+ tests.

Exposes JSON-RPC 2.0 tools that let AI agents scan Base L2 lending positions approaching liquidation, simulate flash-loan-backed debt rescue plans, and generate the calldata needed to repay Morpho Blue and Aave v3 debt while avoiding the 5% penalty. Agents and builders can also attach a referral wallet to collect an instant 0.05% USDC revenue share paid atomically in the same block.

Enables AI agents to build, validate, query, and render 3D homes and object scenes from a single JSON scene file over MCP, with browser walkthroughs for people.

This MCP server lets an agent run local binary inspection on ELF, Mach-O, PE, APK, IPA, ASAR, WebAssembly, and firmware targets — pulling symbols, sections, classified strings, disassembly, and mitigation posture, and flagging dangerous imports and CWE patterns. It exposes eight stdio JSON-RPC tools (with no external API keys) that feed a multi-agent swarm for attack-surface mapping and exploit-chain synthesis.

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.