mcp-compressor MCP Server
atlassian-labs/mcp-compressor
[](https://agentrank-ai.com/tool/atlassian-labs--mcp-compressor/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) An MCP server wrapper for reducing tokens consumed by MCP tools, available in typescript, python, and rust
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
atlassian-labs/mcp-compressor is a Rust MCP server licensed under Apache-2.0. An MCP server wrapper for reducing tokens consumed by MCP tools, available in typescript, python, and rust
Ranked #1304 out of 24846 indexed tools.
In the top 6% of all indexed tools.
Has 11 contributors.
Ecosystem
Score Breakdown
131 stars → growing community
Last commit 17d ago → recently updated
8/11 issues closed → decent issue management
11 contributors → active community
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
# mcp-compressor `mcp-compressor` helps agents use large MCP servers without spending huge amounts of context on tool descriptions and schemas. It can run as a CLI MCP proxy, or be embedded directly from Python, TypeScript, or Rust. - **Documentation**: <https://atlassian-labs.github.io/mcp-compressor/> - **Repository**: <https://github.com/atlassian-labs/mcp-compressor/> - **Blog**: <https://www.atlassian.com/blog/developer/mcp-compression-preventing-tool-bloat-in-ai-agents/> ## Why mcp-compressor? A powerful MCP server can expose dozens or hundreds of tools. Each tool has a name, description, input schema, and sometimes large nested JSON Schema details. Sending all of that to a model up front can waste thousands of tokens before the agent has done any useful work. For example, large public MCP servers can spend thousands or tens of thousands of tokens on tool descriptions alone. That creates three problems: - models spend context on tools they may never call, - cost increasesRead full README on GitHub →
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