Semantic code intelligence MCP server that cuts AI token usage by ~94% with pre-computed knowledge graphs.
qartez-mcp is easy to set up with strong trust signals. Check agent compatibility and use-case fit before adding it to your workflow.
gh repo view kuberstar/qartez-mcp --webOpen the official README and confirm the supported install method.
Add the server entry to your MCP client config.
Restart your agent and verify that the server tools appear.
Repository setup guidance
Strong trust signals; still review the README and permissions before production use.
Last commit was about 106 days ago.
56 GitHub stars indicate community interest.
0 open issues signal maintenance load.
Connect any AI model to 1200+ integrations (MCP, CLI, API)
An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent & Tool calling, and supports plugins.
Official Microsoft Learn MCP server and CLI tool providing real-time, trusted Microsoft docs and code samples to AI agents.
Qartez is a tool that helps AI coding assistants understand your codebase without reading every file. It pre-builds a map of your code's symbols, imports, and dependencies, so the AI can answer questions and make changes using far fewer tokens. This saves money and speeds up development.
Qartez MCP is a Model Context Protocol server that provides semantic code intelligence for AI coding agents like Claude Code. Instead of relying on traditional tools like grep and find, Qartez pre-computes a knowledge graph of your repository containing symbols, imports, call edges, blast radii, PageRank, git co-change, and cyclomatic complexity. This allows AI agents to query the codebase directly, reducing token usage by approximately 94% compared to reading files line by line. The server exposes 37 MCP tools covering project mapping, symbol search, impact analysis, modification guard, and more. It supports 37 programming languages and is designed from the ground up for consumption by language models, not humans. Qartez includes three binaries: qartez (the MCP server), qartez-guard (a modification guard that prevents breaking changes), and qartez-setup (for easy installation and IDE configuration). It runs on macOS, Linux, and Windows, with pre-built binaries for x86_64 and arm64 architectures.
Semantic code intelligence MCP server that cuts AI token usage by ~94% with pre-computed knowledge graphs.
AI-assisted developers using Claude Code, Cursor, or other MCP-compatible agents., Engineering teams looking to reduce AI token costs and improve code understanding., Developers working on large, complex codebases with many interdependencies.
The setup section provides repository-level starting guidance, not a guarantee of an independently verified installation. Check the official README and release notes.
The tool requires access to the entire repository to build its index, which may include sensitive code. Pre-computed indexes are stored locally; ensure proper access controls if used in shared environments.
Similar or complementary options to evaluate include metorial, mcp-context-forge, Microsoft Learn MCP Server.
Aug 20, 2026
NOASSERTION license detected.
3 security/trust notes recorded.
Setup difficulty is 2/5.
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