MCP servers that ship as code — a repository or a package you install and run locally (usually over stdio). They have no hosted endpoint, so we cannot probe or grade them: instead each one shows its repository, install command, license, stars and when it was last updated.
Collected from GitHub repositories and npm, PyPI, Cargo, Go, Maven, NuGet and RubyGems packages tagged as MCP servers, the official MCP Registry, Docker's MCP catalog, ModelScope, Baidu MCP World, Cline and other public directories; one entry per repository. A server that also offers a hosted endpoint is listed under Remote instead. These entries are not counted in our reachability, verification or readiness statistics.
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Local-first token reduction engine and MCP server: gives AI coding agents dependency skeletons (types, signatures, exports) instead of full files, so they read far fewer tokens.
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AsterMind MCP server - on-device RAG token reduction (stdio, 10 tools)
MIT ★ 1 -
Code Search and MCP server for AI coding agents. Instant Token Reduction.
Apache-2.0 ★ 9 -
Framework-aware code intelligence for LLM agents. Indexes Java, Python, TypeScript, Go, Scala into a verified call graph via tree-sitter + Rust. MCP server, Haiku sub-agent, and git hooks included. 68–95% agent token reduction.
MIT ★ 1 -
ATR: Automation for Token Reduction. An MCP proxy that hides tool lists and shrinks tool results so your AI uses fewer tokens.
pypi MIT -
stumpgithub.com/hegner123/stumpupdated this year
Token-efficient directory tree visualization MCP server in Zig - optimized for LLM consumption with 50%+ reduction vs standard tree output
MIT -
Local-first Python SDK for AI agents: Shadow DOM flatten, Action Map, SchemaSnap, form fill, security scan, MCP (64–97% token reduction)
MIT ★ 10 -
MCP server for efficient context sharing between Claude Code sub-agents with 96% token reduction via action-based tools
npm MIT -
Codex plugin and MCP server for TypeSafe Jev decisions and recoverable context reduction, with optional local Laya-MLX and token/time measurement tools.
NOASSERTION ★ 1 -
Codex plugin MCP server (codex-plugin-mcp) for token efficiency, token reduction, context compression: exact-recoverable terminal, file, project, web, memory.
MIT ★ 4 -
Free, open-source, token-efficient local alternative to Firecrawl with native MCP Server for LLMs (>73% token reduction).
MIT ★ 5 -
recursive-thinking-mcpgithub.com/parth3930/recursive-thinking-mcpupdated this year
Token-efficient recursive thinking MCP server for AI agents. Achieve production-ready solutions through iterative refinement with 70% token reduction. Perfect for Claude, AI problem-solving, and complex task automation.
npm MIT -
mcprunegithub.com/hamr0/mcpruneupdated this year
MCP middleware that prunes Playwright accessibility snapshots for LLM agents. Zero ML, 75-95% token reduction, all refs preserved.
npm MIT -
Universal, deterministic context compressor for AI coding agents & IDEs (Claude Code, Cursor, Antigravity, Codex, Gemini, Hermes) — 88.3% token reduction, lossless TOON v2 JSON tables, AST code skeletonization, and SQLite WAL + Zstd CCR (#c1) recovery over stdio MCP.
pypi MIT ★ 3 -
mcp-codebase-indexgithub.com/MikeRecognex/mcp-codebase-indexupdated this year
17 MCP query tools for codebase navigation — functions, classes, imports, dependency graphs, change impact. Zero dependencies. 87% token reduction.
AGPL-3.0 ★ 63 -
High-performance MCP server for USPTO Enriched Citation API v3 with AI-powered data extraction, token-saving context reduction, progressive disclosure workflows, and seamless cross-MCP integration
MIT ★ 7 -
@csc-protocol/token-saveractive
Autonomous AI agent tool and MCP server for semantic token compression and L402 edge solvency clearance.
npm UNLICENSED -
Cuts Claude Code and LLM token usage by 60-85% via AST navigation, deduplication, and context-budget optimization.
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Universal context optimization for AI coding assistants.
npm MPL-2.0 -
Save up to 80% tokens when AI reads code — MCP server for token-efficient code navigation, AST-aware structural reading instead of dumping full files into context window
npm MIT -
json-to-toon-mcp-servergithub.com/your-username/json-to-toon-mcp-serverupdated this year
MCP server for converting JSON to TOON (Token-Oriented Object Notation) format - saves 30-60% on AI tokens
npm MIT -
tokensavergithub.com/pozii/tokensaverupdated this year
MCP server that cuts AI agent token costs by up to 97% — compression, caching, pruning, web extraction
Apache-2.0 ★ 1 -
Token-slimming AST code outliner, log compressor & context budget analyzer for AI coding agents (Cursor, Claude, Cline, Antigravity). Slashes token usage & LLM API bills up to 85%.
MIT -
five-mcpgithub.com/kiro0x/five-mcpupdated this year
160,000 deductively-derived JSON constraints that eliminate LLM persona drift. Measured: 0 breaks in a 120-turn pressure test.
pypi MIT -
pcp-enginegithub.com/rishi-banerjee1/prompt-control-planeupdated this year
PCP — the prompt quality engine. Deterministic scoring, compilation, cost estimation & governance for AI prompts. Zero LLM calls.
npm Elastic-2.0 -
cctx-optimizergithub.com/anil7948/cctxupdated this year
Reduce Claude Code token usage by 70-90% with cross-session memory and four-layer optimization: semantic codebase indexing, PostToolUse tool compression, turn summarization, and session consolidation. MCP server powered by Ollama — zero API calls, runs en
npm MIT -
@blanklogic/refinery-mcpupdated this year
Clean context before AI sees it — BlankLogic Refinery MCP for Cursor and Claude Code (local, no upload).
npm UNLICENSED -
claude-prompt-optimizer-mcpgithub.com/rishiatlan/prompt-optimizer-mcpupdated this year
The control plane for AI prompts — deterministic scoring, policy enforcement, audit & governance via MCP. Free tier included.
npm Elastic-2.0 -
Local-first vision-language pipeline inspired by VL-JEPA. Compress images, text, conversations, and RAG documents locally via Ollama before sending to any LLM API. Deterministic, fact-preserving token optimizer plus MCP server, FastAPI server and video processing.
pypi Proprietary -
Token and context optimization for AI coding agents with smart compression, retrieval, recovery, routing, and MCP integrations.
MIT ★ 1 -
cctxgithub.com/anil7948/cctxupdated this year
Reduce Claude Code token usage by 70-90% using a free local LLM (Ollama). MCP server + Stop hook with codebase indexing, tool output compression, and turn summarization.
MIT ★ 3 -
Decoupled local-SLM pre-processing and routing layer for MCP and cloud LLMs. Intercepts, distills, and routes prompts locally with Ollama to cut token costs and protect monthly quota.
npm MIT ★ 3 -
MCP server that shrinks logs, JSON, docs and web pages before your AI reads them. Offline, deterministic, ~3ms, no API key. 66% fewer tokens on a mixed dev corpus, 90%+ on logs.
NOASSERTION ★ 25