"WEMO" matching MCP servers:

A demonstration implementation of the Model Context Protocol server that facilitates communication between AI models and external tools while maintaining context awareness.

A simplified Model Context Protocol server in Python that reads text input and generates humorous responses, with support for Docker and Azure deployment.

Provides persistent, client-side-encrypted memory for AI coding assistants via SAIHM, enabling tools to remember, recall, and forget with provable erasure.

A demonstration project that uses Cloudflare Workers MCP to create custom AI tools that can be integrated with Claude, Cursor, and other AI assistants supporting the Model Context Protocol.

Serves Agent Skills over MCP using the SEP-2640 Skills Extension, enabling skills discovery, retrieval, and resource reading via MCP.

Enables agents such as ChatGPT to subscribe to events happening behind an MCP server (for example, order.created with filters) and receive them as signed webhooks without the builder implementing delivery itself. Hookdeck Outpost handles filtering, Standard Webhooks signing, retries, and delivery to each subscriber's callback URL.

Provides non-custodial, post-quantum encrypted memory for AI agents, enabling portable memory across models with provable erasure.

Enables AI agents to browse, list, buy, review, and get paid for digital goods through MCP tools, including balance, ledger, checkout-link, upload, and payout operations. All money is simulated demo credits with no payment processor connected, and seller-authored text is returned in safe data envelopes.

Enables contract-driven trip booking through HAPI Capability Graphs and Arazzo workflow tools, letting clients plan and invoke allowed capabilities locally. It resolves clear intent despite ambiguous wording by using declared vocabulary and verified facts.

Enables stateless human-in-the-loop DevOps automation, demonstrating MCP SEP-2322 multi-round trip requests for emergency database migration authorization.

Exposes ontology reasoning and domain-adapter tools so agents can perform capability matching, task orchestration, assignment, consistency checking, and generic OWL/SPARQL queries against loaded ontologies.

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 natural-language analysis of insurance customer migration data through CrewAI agents, providing tools for querying renewals, churn, competitor returns, and feature adoption.

A self-aware, AI-powered MCP server that acts as a personal medical education assistant for African students, understanding natural language and autonomously managing reminders, data bundles, and medical knowledge retrieval.

Enables remote MCP client connections with WorkOS AuthKit authentication, supporting organization-centric user management and permission-based tool access control.

Enables interaction with the Agent Legion platform through MCP. Provides tools such as tool_say_hi to demo the server's capabilities.

Enables AI agents to safely mutate business state by demonstrating phase-gating, validation-before-mutation, and structured audit logging in a toy inventory and purchase order system.

Enables AI assistants to interact with a commercial management system through controlled capabilities for querying orders, analyzing invoices, summarizing customer activity, and creating orders, with role-based access control and audit trails.

Provides MCP tools to enforce spend policies (allow, deny, step-up, allowlist) on agent wallets with an immutable audit trail.

A hands-on demonstration project that teaches the Model Context Protocol (MCP) through Python code, allowing users to understand how AI models interact with their context through a provider-agent architecture.