"Samsung Pay" matching MCP servers:

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.

Enables AI agents to store and retrieve persistent memory across sessions and machines, and to pay any x402 API while keeping a signed, offline-verifiable ledger of purchases and spending.

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

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.

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.

Memory for AI agents that keeps every claim with the source it came from, the date it was asserted, and a confidence you can re-weight per source, so your agent can say where a fact came from. Updates supersede or retract instead of overwriting, so you can replay what the store believed on any past date and review contradictions as lint findings.

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

The whole Wicked suite for agents in one MCP server: 107 tools across trading data, prediction markets, web search, crypto news, wallet portfolio, DeFi and token risk, SEC filings, agent identity, reputation, a tool registry, hallucination checks, memory and x402 paywalls. No signup; pay per call in USDC on Base.

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.

A remote MCP server that enables AI coding agents to search and retrieve context from imported AI chat history (ChatGPT, Claude, Codex, Claude Code) stored in Google Drive, with zero server-side storage and OAuth-based privacy.

Enables VS Code agent mode to search and retrieve context from your LLMemory vault of AI conversations (ChatGPT, Claude, etc.) without copying and pasting.

Enables an AI agent to recall past approvals, edits and rejections that are similar to the task at hand before drafting, and to record each new decision along with the human's reason. Memory lives in a local Postgres (PGlite + pgvector) store, so corrections carry across sessions without hosting anything.

Enables an AI agent to search a folder of markdown notes, follow links and backlinks, and safely rename notes while rewriting every link to them.