"A server for finding information about the % token" matching MCP servers:

MCP server that reduces token consumption in AI coding assistants by up to 90% via structural reads, PreToolUse hooks, and tp-\* subagents.

Token-safe code search for AI agents: queries the language-server index (clangd / Roslyn / tsserver / pyright) instead of grep and returns a token-capped file:line list — ~20x fewer tokens. Symbol-level editing + a grep→index rewrite hook. Local-only, no IDE.

An MCP server that provides structural codebase indexing and surgical query tools to drastically reduce token usage through symbol-level searches and transitive impact analysis. It supports multiple languages and integrates with git to help AI agents understand code dependencies and the impact of changes in sub-millisecond time.

Enables AI agents to obtain a compressed code context where the active file is fully included and dependency files are reduced to type signatures, interfaces, and exports, cutting token usage while preserving code shape.

Enables coding agents to retrieve token-budgeted, source-hashed code context from explicitly registered local repositories via read-only MCP tools, reducing broad repository crawling while providing structure, symbols, and impact slices.

Enterprise-grade code intelligence server for AI assistants that analyzes codebases for due diligence, tech debt, security vulnerabilities, and code quality.

Enables analyzing and optimizing context window token usage by measuring, compressing, and eliminating waste from MCP tool definitions.

Bridges VSCode's Language Server Protocol with MCP to give AI assistants instant access to code intelligence, delivering 100-1000x faster responses with 90% fewer tokens than traditional text-based searching. Provides 17 production-ready tools for navigation, refactoring, diagnostics, and code analysis.

An MCP server that gives AI agents Angular template awareness via compiler-backed tools, providing component contracts, diagnostics, and version-specific facts while saving tokens by returning concise JSON instead of entire source files.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

Enables MCP-compatible AI clients to inspect Godot project and editor state, observe opted-in running scenes, manage processes, and apply permission-scoped guarded edits. It starts read-only and exposes additional capabilities only through explicit command-line flags.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

An MCP server for interacting with the Rell Language Server Protocol interface. It enables LLMs to query LSP Hover and Completion providers for Rell projects.

Codebase Q&A agent with git-history awareness. Explore a repo with list_files, read_file, and search, plus git log, blame, and diff and a repo map to answer "why did this change?" questions. Runs locally as an MCP server for Claude Code and other MCP clients.

Enables LLM-powered agents to generate, execute, and analyze Alloy modeling language code for software modeling and formal verification. Provides tools to run Alloy models, access documentation and examples, and generate models from system descriptions.