"Common Lisp" matching MCP servers:

Enables MCP clients to submit a group’s favorite movies, books, restaurants, artists, or TV shows and receive a fairness-ranked common pick, three alternatives, and per-person reasons using Qloo affinity insights.

Enables AI assistants and local workflows to run Jev-powered tools that judge speeches line by line, audit drafts against goals, bisect hard-to-test bugs, simulate common-sense physics, score note pairs, and ask arbitrary typed questions cheaply.

Connects AI coding agents in the Antigravity CLI to native language servers for C#, C/C++, TypeScript/JavaScript, and Python through MCP tools, enabling precise symbol navigation, diagnostics, references, refactoring previews, and other code intelligence.

Bridges MCP-stdio clients to a remote emoji service, enabling emoji search, details, random picks, Emoji Kitchen mashups, and LLM-powered recommendations and replacement suggestions.

Enables clients to optimize prompt prefix caching by matching longest common token prefixes with a radix trie, eliminating redundant prefill computation and reducing time-to-first-token.

Enables inference engines to match longest common prompt token prefixes via a radix trie, so cached KV-cache blocks are reused instead of re-prefilled. This eliminates redundant prefill computation and lowers time-to-first-token, alongside paged attention allocation, speculative decoding verification, INT8 quantization, and latency telemetry.

A remote MCP server that returns group-aware recommendations scored against each person's taste profile, plus taste-tag lookups, so any agent can plan options that fit everyone rather than the average.

Serves read-only tools over MCP that let any assistant explore the music, films and shows of a resident's youth, plan reminiscence sessions and rank lounge films by each resident's tastes. It matches family favourites and hometowns to culturally fitting picks, ranks shortlists for every resident and finds common ground between residents and carers, while keeping names and care notes out of every request.

A lightweight MCP server that bridges AI agents with a local ComfyUI instance to generate and iteratively refine images, audio, and video through conversational tool calls.

MCP server for AI agents to conduct multi-LLM roundtable discussions, returning structured common, divergent, and unique perspectives.

An MCP server that gives Claude hands-on access to quantum computing via Qiskit, enabling building circuits, simulation, statevector inspection, transpilation, and optional execution on real IBM quantum computers.