"Star Trek" matching MCP servers:

Enables graph pathfinding and network analysis through MCP, including Dijkstra/A* shortest paths, topological dependency resolution, maximum flow, minimum spanning trees, and PageRank centrality for agent planning.

Enables external agents to coordinate structured MIP research and coding workflows, load method cards, templates, and skills, and receive COPT-backed experiment feedback with budgets and verification.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

A language-neutral runtime for the SEP-2663 task lifecycle and io.sdar/taskExecution Provider Profile, delegating resource facts and side effects to versioned gRPC/Protobuf adapters. Implemented in strict TypeScript, it provides durable scheduling, recovery, and a full test suite for conformance.

Enables AI assistants to inspect .sim files and solver logs without a licence, search local STAR-CCM+ documentation and Java API references, and run checked Java macros against an open simulation session.

A foundational template for building MCP servers in Python using Streamable HTTP transport. Provides example implementations of tools, resources, and prompts to help developers create custom MCP integrations for AI assistants.

A local stdio MCP server that lets agents submit and manage Python/notebook jobs on Kaggle and Google Colab, with quota-aware provider recommendation, job listing/reconciliation, downloads, and cancellation. It runs in a safe mock mode by default and requires double-gated flags before any real GPU or CCU-billed work is submitted.