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

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

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.

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.

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).

Exposes design system component documentation to LLM clients via MCP, allowing listing and retrieving component contexts from Markdown files with YAML frontmatter.

Enables AI assistants to interact with Square's Connect API through the Model Context Protocol standard, allowing for operations like managing customers, processing payments, and handling inventory.

Use multiple Cerebras models from Claude Desktop & Claude Code with automatic model selection.

Autonomous DeFi yield for AI agents on Base. Query APY rates, agent status, payment splits, and referral stats. 4 read-only tools + 1 resource.

Enables AI agents to understand, inspect, create, validate, build, and document Jekyll component frameworks through Jekyll-aware tools, resources, prompts, sandboxed filesystem access, and configurable write modes.

An MCP server that scans React and Vue projects, extracts component metadata (props, slots, events, imports, usage), and exposes it to AI coding agents via structured tools.

This MCP server publishes commit-bound proof summaries to a specified HTTPS webhook, featuring fail-closed writes and a clear authority boundary for safe external actions.

Enables AI to precisely use local Vue components by extracting their Props, Events, and Slots via AST analysis.

This server facilitates the invocation of AI models from providers like Anthropic, OpenAI, and Groq, enabling users to manage and configure large language model interactions seamlessly.

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

An MCP server for managing contextual data as markdown files with metadata, enabling agents to save, retrieve, search, and delete contexts using simple CRUD operations.

Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.