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.

CLI for the Guren framework: scaffolding (make:*, add), migrations, codegen, and the check, audit and gate commands a coding agent runs to verify its work.

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.

Automated index of Claude Code plugins and adoption metrics across GitHub repositories, powered by a Node.js/TypeScript crawler

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.

Enables an AI assistant to query Plaid-synced bank data stored locally in SQLite — balances, transactions, spending, cash flow, recurring charges, and liabilities — plus bounded read-only SQL and local CSV/JSON exports, all over local stdio with no hosted service or listening port.

Enables AI clients to search Korean court auction real estate by court, region, usage, sale date, appraisal/minimum price, and failure count; fetch case details; collect and resume jobs; and export results to Excel, CSV, and JSONL.

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 MCP clients to inspect PDF structure and extract object-level data such as characters, words, tables, images, fonts, and metadata, with JSON/CSV export and image retrieval.

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 offline King James Version Bible lookup, passage retrieval, word and phrase search, deterministic verse-of-the-day access, and book/chapter listing for AI assistants. All tools are read-only and return citable references with structured JSON.

Enables Claude to plan search-and-rescue operations on CalTopo maps by measuring terrain, staging areas, hasty search lines, parking, helicopter landing zones, egress routes, walking-time rings, hospitals, and urban assignments, and by exporting results as GeoJSON draft assignments. It is read-only and returns facts for human decision-making.

A Claude Code plugin that stops vague prompts before they run. Detects your stack, asks targeted questions, and forges a structured prompt. Zero credits wasted.

MCP server that checks a website's AI-search (GEO) readiness: robots.txt access for 16 AI crawlers (GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot, Google-Extended, Bingbot...), JSON-LD schema, llms.txt, sitemap and basic SEO tags. Python, stdio, MIT.

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.

Provides an MCP server for deterministic game-theoretic optimization, enabling regret-matching equilibrium computation and payoff-matrix analysis with IESDS dominance pruning via JSON tool results.

Enables MCP clients to perform speculative tree-search action prediction and prefetching using Laplace-smoothed Markov transitions, returning deterministic JSON tool results.

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 discovery of official DHS country, survey, and indicator metadata; retrieval of public aggregate estimates; assessment of comparison risks; and export of auditable CSV, JSON, Excel, or executable notebook bundles.

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.