"Information about computer usage" matching MCP servers:

An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

Enables MCP clients to run Cline CLI prompts and isolated repository-wide analyses, returning terminal text responses with model, duration, and usage/cost.

Wraps the cursor-agent CLI to provide cost-effective tools for repository analysis, code search, planning, and editing. Offloads heavy thinking tasks from the host AI to reduce token usage while maintaining precise, scoped workspace operations.

Enables coding agents to navigate and query source code by providing context, symbols, and call graph information through a graph index.

A local MCP bridge that lets ChatGPT control opencode sessions for code modification, file reading, and repository management on your own computer.

A local project intelligence, batch coding, and self-learning engine for Codex that enables task-level batch coding, reduces token usage, and automatically learns skills.

Context compiler for AI coding agents that indexes TypeScript codebases to extract and serve only the relevant symbols and files for a task, reducing token usage and search overhead.

Enables MCP-compatible coding agents to run the local Antigravity CLI as a coding agent, manage conversation context and common options, and inspect usage, quota, models, version, help, and read-only slash commands.

Enables external MCP clients to drive DeepSeek Harness agents for real coding tasks, providing tools for task execution and queueing, session management, sandboxed file access, preset switching, and usage statistics.

Implements Agentic Context Engineering to create self-improving AI coding assistants that learn from execution feedback and build persistent knowledge playbooks. Reduces token usage by 86.9% while improving code accuracy by 10.6% through incremental context updates.

Enables coding agents like Cursor to access Figma design data, fetch layout and styling information, and implement designs in any framework.

Provides file caching and diff tracking for AI coding agents, reducing token usage by returning changes or confirming no changes instead of full file contents on repeated reads.

https://gopls-mcp.org/ MCP server for golang projects development: Expand AI Code Agent ability boundary to have a semantic understanding and determinisic information for golang projects.

Lets Claude Code delegate tasks to the OpenCode CLI, choosing cost-effective models by intelligence tier and tracking usage.

Enables AI coding agents to efficiently query code context via a symbol graph, reducing token usage by up to 20x.

Provides AI coding agents with persistent architectural memory of codebases, enabling impact analysis, test generation, and code generation with reduced token usage.

Local-first MCP server that indexes all projects on your machine and provides coding agents with briefings about each project's stack, services, and run instructions, so they can start sessions with context across all repos. No cloud, no accounts, no telemetry.

MCP server that enables Claude Code to communicate with other Claude Code agents over HTTP, allowing users to ask questions about remote codebases or delegate coding tasks.

A secure, local-first MCP coding and computer-use harness for ChatGPT and Codex, enabling guarded file operations, durable terminals, Git review, local skills, and macOS computer control.