"Optimizing AI Model Thinking, Token Usage, and Context Size" matching MCP servers:

Local-first documentation for AI agents

An MCP server serving a curated corpus of thinking techniques for AI agents, with tools to classify intents, find and apply techniques, and verify their effectiveness.

Provides verified, up-to-date model IDs, pricing, and specs for over 100 models across 19 providers, preventing AI agents from using outdated or hallucinated model names.

A Model Context Protocol (MCP) server that injects 'Just-in-Time' context into AI conversations based on file paths and glob patterns.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

Automatically analyzes project dependencies to discover and download the most relevant documentation, enabling developers to quickly set up comprehensive project context.

Provides LLMs with secure, read-only access to local documentation by scanning directories, extracting content from PDF, DOCX, Markdown, and text files, and performing keyword searches.

Provides context about Toon Boom Harmony and its scripting API, enabling AI assistants to access Harmony's API documentation and help developers work with Harmony's scripting capabilities.

Local-first MCP server that gives AI assistants codebase intelligence—code graph, drift analysis, vulnerability attribution, and version-correct library docs—all from the user's machine.

An MCP server that enables AI assistants to manage Context Repo prompts, documents, and collections with semantic search and progressive disclosure navigation.

Provides real-time, version-pinned documentation from 57+ AI/ML libraries to LLMs, preventing hallucinated APIs by fetching current docs and changelogs directly from GitHub.

A local-first MCP server that turns a .context/ folder of markdown files into a searchable knowledge layer for AI coding agents.

Provides project-aware context for coding agents by selecting relevant AGENTS.md, docs, module paths, and decision records based on task, reducing redundant context loading via MCP stdio.

MCP server that stores and queries shared company context, strategic spines, documents, and decision traces with citations and versioning.

Enables semantic search of project documentation using hybrid vector and full-text search with fast and deep query modes for immediate results or complex multi-round synthesis.

Provides a live, audited catalog of AI models from NVIDIA NIM, OpenRouter, Nous Portal, and other providers, enabling search, retrieval, and usage examples via MCP tools and resources.

A thin, local, read-only MCP gateway that exposes governed context documents and producer manifests as logical resources, enabling AI clients to access them without arbitrary filesystem access.

Provides AI agents with architecture decision records, project conventions, and real codebase usage data so they can understand why, when, and where to use design system components.

This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.

Enables searching and retrieving Confluence pages, listing children, and updating pages as drafts, integrating Confluence documentation as context in Claude Code.