Building an AI Agent from Scratch

A Model Context Protocol server that provides access to Redis databases. This server enables LLMs to interact with Redis key-value stores through a set of standardized tools.

Ready for a new way to bill pay? Pay any bill in a snap, right from a chat. Describe or snap a photo of your bill (electric, water, gas, internet, phone, medical, credit card, rent, parking tickets, traffic violations and more) and Papaya reads it, then hands you a secure link to pay by card. Fast, secure, and no juggling twelve logins, with full or partial payments and status updates. Powered by Papaya (papayapay.com).

Host the HTML or Markdown pages your AI generates and share each as a link with comments, versioning, and access control. Create, update, and organize pages and read reviewer comments over MCP.

ContextBridge (CB) is a local-first retrieval layer that sits between your codebase and your AI coding agent. Instead of pasting raw source files into context or letting the AI guess which files matter, CB indexes your codebase's real structure (via Graphify) and returns a compact, ranked result — owner file, related files, key symbols, and dependency chains — grounded in your actual code. A typical response is ~4–8 KB instead of the 100+ KB of raw source an AI would otherwise need to read to answer the same question — roughly a 96% cut in input tokens sent to your cloud AI, with zero hallucinated file paths or method names.

Persistent Adaptive Planning Intelligence - structured loop engineering for AI coding assistants, with memory that persists across sessions, tools, and teammates.

BlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.

Official Firecrawl MCP Server - Adds powerful web scraping to Cursor, Claude and any other LLM clients.

Language models generate; Concordance verifies. The verify tool checks a claim deterministically (no model in the loop) and returns HOLDS / BROKEN / INCOMPLETE with the worked reasoning and a sealed receipt (content_hash + cite_url) that re-fetches byte-identical or not at all. Also: ranked search over an ~11k-record library, seal_fetch to re-verify any receipt, redact to strip PII before text travels, and a sealed connection graph. Runs sovereign/offline too (stdlib-first Python). A public false-positive benchmark covers every domain: the engine has never sealed a falsehood. 38 tools live; remote endpoint at https://narrowhighway.com/mcp.

An MCP server implementation for retrieving information from the AWS Knowledge Base using the Bedrock Agent Runtime.

Channel management and messaging capabilities

Playwright MCP server