"Amazon Pay" matching MCP servers:

Enables management of Amazon Bedrock Knowledge Bases including creation, data source configuration, document ingestion, and RAG (Retrieval-Augmented Generation) queries with support for multiple embedding models and custom parsing/chunking strategies.

MCP server that gives AI agents persistent, tenant-scoped memory with semantic search and consolidation, using CockroachDB vector indexes and Amazon Bedrock embeddings.

Headless document processing for AI agents. Invoice extraction, contract analysis, and Dutch business verification. Pay-per-use via X402 on Solana. No API keys needed.

Converts family notices (hospital, government, insurance, delivery) into action cards with confirmed facts and pending verifications, enabling collaborative family confirmation and completion.

Serverless document and media processing with AI chat. Upload documents, images, video, and audio — extract text with OCR or transcription — query using Amazon Bedrock.

Enables AI agents to store, read, extend, and share encrypted persistent memory, with pay-per-use access via x402 payments on Base.

MCP server giving AI agents real-time web search, page scraping, company intelligence, email discovery, local lead generation, and a persistent knowledge graph. Pay only for what you use, no subscriptions.

Pay-per-use semantic memory for AI agents with cryptographic attestation. Vector embeddings with SHA256 commitment, secp256k1 signature, and Lightning invoice.

Provides an MCP server that gives LLM agents an evolutionary memory: entries pay upkeep and survive only if they earn their keep through measured outcomes, with tools for querying, settling, and managing memory.

Enables semantic and keyword search across AI work sessions, learnings, reflections, failures, research, and relationships stored in PAI's MEMORY directory.

MCP server for enabling data extraction and context retrieval for agents, storing information in a knowledge graph using Amazon Neptune or FalkorDB.

Safe write access for AI agents. Stellar Jay is an append-only business fact store: every change is kept, attributed to the agent that made it, and can be undone. Agents record, correct and retract facts, read entities, and reverse a bad run with undo_changes. Self-host with stellarjay-mcp (Go, AGPL) or connect to the hosted AvianSuite server at https://mcp.aviansuite.com/mcp.

Gives your agent a private Kinematic Drive: a deterministic memory engine for sub-millisecond exact recall over code and docs with no hallucination. Also provides self-serve checkout and metered pay-per-call tools for AI agents.

Structured knowledge API for AI agents — fractal knowledge graphs, signal datasets, authority evidence reviews, open problems, and capability specs. Pay-per-query or subscription via Lightning, Stripe, or USDC.

Enables AI agents to inspect ontology schemas, search typed objects, and execute read-only SPARQL queries against an RDF triple store.

Connects AI coding agents to Google NotebookLM, enabling querying notebooks, adding sources, and generating artifacts like reports, podcasts, and slide decks.

MCP server for the whole Wicked suite: trading data, DeFi protocol health, token risk, brokerage sync, agent identity, reputation, a tool-reliability registry, hallucination checks, persistent wallet-scoped agent memory (store, semantic search, versioned history, hard delete) and x402 paywalls. 75 tools. Pay per call with x402 on Base, or use free API keys.

A read-only MCP server over a published model catalogue that lets agents search and resolve models, fetch overlay profiles, definitions and citations, and check memory records against a governance overlay through the same code path as the CLI.

Wctx is an MCP server that captures structured, evidence-backed context from completed coding agent sessions and serves it to future sessions, enabling cross-repository knowledge reuse without cloud dependencies or embeddings.

Provides persistent memory, calendar integration, task management, and proactive assistance for Alexa+ through the Model Context Protocol.