"Proof-of-Concept Examples for Multi-Component Processes (Model Context Protocol)" matching MCP servers:

MCP server enabling real-time weather queries via Tavily API and internet usage data by country via MongoDB.

A basic Python implementation of a Model Context Protocol server for educational purposes, using FastAPI and WebSockets.

A production-ready MCP server template that connects LLMs and AI agents to external data, tools, and services with built-in OAuth 2.1 authentication, Redis-backed session management, and a modular tools engine.

Supply chain risk scoring for npm, PyPI, and GitHub repos

MCP server for exploring and querying Supabase databases with interactive React widgets for schema browsing, table viewing, and SQL execution.

A Python-based server for managing and analyzing code context for AI-assisted development. Provides real-time code analysis, project structure analysis, dependency tracking, and secure API endpoints.

Local MCP server that lets Claude Code delegate bounded, read-only tasks to external AI models (Codex, Grok, local OpenAI-compatible servers) via CLIProxyAPI.

An MCP server that exposes tools for sub-agent style reasoning across multiple LLM providers, enabling delegation of prompts to various models and running critique loops, debates, red-teaming, and answer ranking.

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

Enables agents to prove and verify that a real, unique human performed an action, issuing machine-readable signed credentials with public verification.

Enables LLMs to perform conceptual search over local PDF/EPUB documents using a RAG pipeline with corpus-driven concept extraction and WordNet enrichment.

One MCP server that routes to 12+ AI providers for text, image, and video generation, with smart task delegation, web search, and model comparison—all from the terminal.

An event-driven MCP server that enables agents to share context streams, publish and subscribe to events, manage tasks, and follow protocols, keeping a fleet of agents mutually context-aware in real time.

Records privacy-preserving receipts for AI-assisted tasks and enables optional onchain reward claiming via AIPOU tokens. Integrates with MCP-compatible clients like Claude and Cursor.

Enables AI agents to compose MCP tool calls into Unix-style pipelines, executing complex workflows server-side and returning only the final result.

Connects Codex to local and cloud language models from MoE4All, GLM, DeepSeek, and OpenAI-compatible endpoints through a controlled MCP worker boundary, enabling read-only worker analysis, provider configuration, and VS Code model setup while keeping write authority with Codex.

Summarizes Slack activity and GitLab merge requests with OpenAI to help generate daily standups, weekly reports, or quarterly check-ins.

Verifies blockchain-anchored timestamp proofs entirely on the user's machine, with five tools: hash a file, verify a file against a proof, verify a known hash against inline proof data, explain what a proof asserts, and create a new proof through ProofLedger. Verification recomputes the SHA-256 and walks the Merkle path locally instead of asking the issuer; only create uses the network.

Provides two MCP servers: Variant Authority for managing component variant manifests and Radix Primitives for accessibility composition using Radix UI. Together they serve as the source of truth for design-to-code workflows.

Autonomous M2M compliance and trust APIs for AI agents (KYB, OFAC, VAT, Sanctions checking).