"IBM MCP Context Forge - Model Context Protocol Framework" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Engram is a persistent, long-term memory layer for AI agents and assistants. Claude, ChatGPT, Grok, Cursor and any MCP client share one memory, stored as plain markdown notes: your knowledge base, second brain and AI context in one place. No extraction step: the memory is the note itself, so you can read exactly what your AI remembers and fix it. Edit your memory in Obsidian (real-time sync), the web app, or on your phone. Hybrid keyword + semantic search (RAG over your notes) finds exact strings like error messages, config keys and IDs. Remote MCP server over Streamable HTTP with OAuth 2.1; notes encrypted at rest. Https://engram.page https://youtu.be/rwnPeZ-8Lqo?is=NI-N7BduydGAiZlF https://github.com/engram-app/Engram
Machine-exclusive web distillation MCP server for AI agents. Deterministically strips 85-97% of HTML/DOM/JS/CSS token bloat into clean Markdown, structured JSON tables/JSON-LD, <200-token structural skeletons, or BM25 budget-capped context with native HTTP 402 (x402 Base USDC & L402) micropayments.
Strips 85-97% of HTML/DOM boilerplate into clean Markdown, skeletons, or BM25-ranked RAG chunks.
Cited news for AI agents from AI companies, VC firms, private companies and business podcasts.
The right context at the right time, from the world's leading data providers. One API. 800+ tools.
Fresh context for agents. Ask, search or follow stories. Each fact cites a Synorb Manifest.
Bring your saved preferences, project decisions, and useful context into your next AI conversation.
Free, read-only context retention review for RAG and agent workflows. Supply sanitized text with stable source IDs and a token budget; receive a source-linked context pack, token estimates, and exact excerpt-retention results. No web fetching, account access, model calls or payments. Checks text selection, not factual truth or semantic completeness. No API key required.
Historical market memory for AI agents using semantic vector search across years of financial market data. Discover similar market regimes, price patterns, and market context for quantitative research and algorithmic trading.
Persistent memory and knowledge graphs for AI agents. Hybrid search, context checkpoints, and more.
Context crossmatch: compatibility typing for context ingestion. $0.005/check.
Persistent project context for xAI Grok. IANA-registered .faf format.
LLM & RAG evals: hallucination, eval contracts, semantic tests, tokens & model info. Free, no key.
The context marketplace: expert guided journeys your assistant runs step by step.
The world's first named AI prompt quality score. Score, optimize, and compare LLM prompts before they hit any model. Free tier available. Built on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. x402-native on Base.
Search hub knowledge and memories, read saved context, and create or update hub content.
Tenant-scoped evidence intake and controlled AI context over MCP.
Turn a GitHub repo or docs site into agent-ready context: pack it or search it, over MCP.
One semantic search across your sites, Drive, Notion, email, files and Basecamp.
A high-performance, edge-native Data Refinery Engine built on Cloudflare's serverless AI stack (Workers, Workers AI, D1, KV, Vectorize) designed to continuously ingest unstructured data, refine it into pristine machine-readable structured intelligence, compute semantic diffs, and serve it directly to AI agents via the Model Context Protocol (MCP) and REST APIs.
