An MCP server wrapper for reducing tokens consumed by MCP tools.
mcp-compressor
An MCP server wrapper for reducing tokens consumed by MCP tools.
- Github repository: https://github.com/atlassian-labs/mcp-compressor/
- Documentation https://atlassian-labs.github.io/mcp-compressor/
Overview
MCP Compressor is a proxy server that wraps existing Model Context Protocol (MCP) servers and compresses their tool descriptions to significantly reduce token consumption. Instead of exposing all tools with full schemas directly to language models, it provides a two-step interface:
get_tool_schema(tool_name)- Retrieve the full schema for a specific tool when neededinvoke_tool(tool_name, tool_input)- Execute a tool with the provided arguments
This approach dramatically reduces the number of tokens sent in the initial context while maintaining full functionality.
Why?
MCP servers are exploding in popularity, but their tool descriptions consume significant tokens in every LLM request. For example:
- The official GitHub MCP server exposes 94 tools consuming 17,600 tokens
- The official Atlassian MCP server consumes ~10,000 tokens
With 30k+ tokens just for tool descriptions, costs can reach 1-10 cents per request depending on prompt caching. MCP Compressor solves this by replacing dozens of tools with just 2 wrapper tools, achieving 70-97% token reduction while maintaining full functionality. This enables:
- Adding many MCP servers without blowing out context windows
- Significant cost savings on token-based API pricing
- Support for providing 100s or 1000s of tools across multiple servers to your agent
Features
- Token Reduction: Compress tool descriptions by up to 99% depending on compression level and tool count
- Multiple Compression Levels: Choose between
low,medium,high, ormax - Universal Compatibility: Works with any MCP server (stdio, HTTP, SSE)
- Zero Functionality Loss: All tools remain fully accessible through the wrapper interface
- Easy Integration: Drop-in replacement for existing MCP servers
Installation
Install using pip or uv:
pip install mcp-compressor
# or
uv pip install mcp-compressor
Quick Start
Basic Usage
Wrap any MCP server by providing its command or URL:
# Wrap a stdio MCP server
uvx mcp-compressor uvx mcp-server-fetch
# Wrap a remote HTTP MCP server
uvx mcp-compressor https://example.com/server/mcp
# Wrap a remote SSE MCP server
uvx mcp-compressor https://example.com/server/sse
See uvx mcp-compressor --help for detailed documentation on available arguments.
Compression Levels
Control how much compression to apply with the --compression-level or -c flag:
# Low
mcp-compressor uvx mcp-server-fetch -c low
# Medium (default)
mcp-compressor uvx mcp-server-fetch -c medium
# High
mcp-compressor uvx mcp-server-fetch -c high
# Max
mcp-compressor uvx mcp-server-fetch -c max
Advanced Options
Stdio Servers
# Set working directory
mcp-compressor uvx mcp-server-fetch --cwd /path/to/dir
# Pass environment variables (supports environment variable expansion)
mcp-compressor uvx mcp-server-fetch \
-e API_KEY=${MY_API_KEY} \
-e DEBUG=true
Remote Servers (HTTP/SSE)
# Add custom headers
mcp-compressor https://api.example.com/mcp \
-H "Authorization=Bearer ${TOKEN}" \
-H "X-Custom-Header=value"
# Set timeout (default: 10 seconds)
mcp-compressor https://api.example.com/mcp \
--timeout 30
Custom Server Names
When running multiple MCP servers through mcp-compressor, you can add custom prefixes to the wrapper tool names to avoid conflicts:
# Without server name - tools will be: get_tool_schema, invoke_tool
mcp-compressor uvx mcp-server-fetch
# With server name - tools will be: github_get_tool_schema, github_invoke_tool
mcp-compressor https://api.githubcopilot.com/mcp/ --server-name github
# Special characters are automatically sanitized
mcp-compressor uvx mcp-server-fetch --server-name "My Server!"
# Results in: my_server__get_tool_schema, my_server__invoke_tool
Logging
# Set log level
mcp-compressor uvx mcp-server-fetch --log-level debug
mcp-compressor uvx mcp-server-fetch -l warning
How It Works
The MCP Compressor acts as a transparent proxy between your LLM client and the underlying MCP server:
flowchart TB
subgraph github["GitHub MCP"]
g1["create_pr"]
g2["get_me"]
g3["list_repos"]
g4["get_issue"]
g5["..."]
g6["(+87 more tools)"]
end
subgraph proxy["MCP Compressor"]
t1["get_tool_schema"]
t2["invoke_tool"]
end
subgraph client["MCP Client"]
end
g1 <--> proxy
g2 <--> proxy
g3 <--> proxy
g4 <--> proxy
g6 <--> proxy
t1 <--> client
t2 <--> client
Instead of seeing all tools with full schemas (which are often thousands of tokens), the LLM sees just:
Available tools:
<tool>search_web(query, max_results): Search the web for information</tool>
<tool>get_weather(location, units): Get current weather for a location</tool>
<tool>send_email(to, subject, body): Send an email message</tool>
When the LLM needs to use a tool, it first calls get_tool_schema(tool_name) to retrieve the full schema, then invoke_tool(tool_name, tool_input) to execute it.
sequenceDiagram
participant Client as MCP Client
participant Compressor as MCP Compressor
participant Server as GitHub MCP<br/>(91 tools)
Client->>Compressor: list_tools()
Compressor->>Server: list_tools()
Server-->>Compressor: create_pr, get_me, list_repos, ...
Compressor-->>Client: get_tool_schema, invoke_tool
Client->>Compressor: get_tool_schema("create_pr")
Compressor-->>Client: create_pr description & schema
Client->>Compressor: invoke_tool("create_pr", {...})
Compressor->>Server: create_pr({...})
Server-->>Compressor: result
Compressor-->>Client: result
Compression Level Details
| Level | Description | Use Case |
|-------|-------------|----------|
| max | Maximum compression - exposes list_tools() function | Maximum token savings. Good for (1) MCP servers you want to provide to your agent but expect tools to be used rarely and (2) for servers with a very large number of tools |
| high | Only tool name and parameter names | Maximum token savings, best for large toolsets |
| medium (default) | First sentence of each description | Balanced approach, good for most cases. |
| low | Complete tool descriptions | For tools that are unusual and not intuitive for the agent to understand and use. Using a lower level of compression in these cases provides more context to the LLM on the purpose of the tools and how they relate to each other. |
The best choice of compression level will depend on a number of factors, including:
- The number of tools in the MCP server - more tools, use more compression.
- How frequently the tools are expected to be used - if tools from a compressed server are rarely used, compress them more to prevent eating up tokens for nothing.
- How unusual or complex the tools are - simpler tools can be compressed more heavily with little downsize. Consider a simple
bashtool with a single input argumentcommand. Any modern LLM will understand exactly how to use it after seeing just the tool name and the name of the argument, so unless there is unexpected internal logic within the tool, aggressive compression can be used with little downside.
Configuration with MCP JSON file
To configure mcp-compressor in an MCP JSON configuration file, use the following pattern:
{
"mcpServers": {
"compressed-github": {
"command": "mcp-compressor",
"args": [
"https://api.githubcopilot.com/mcp/",
"--header",
"Authorization=Bearer ${GH_PAT}",
"--server-name",
"github"
],
},
"compressed-fetch": {
"command": "mcp-compressor",
"args": [
"uvx",
"mcp-server-fetch",
"--server-name",
"fetch"
],
}
}
}
This configuration will create tools named github_get_tool_schema, github_invoke_tool, fetch_get_tool_schema, and fetch_invoke_tool, preventing naming conflicts when multiple compressed servers are used together.
With compression level:
{
"mcpServers": {
"compressed-fetch": {
"command": "mcp-compressor",
"args": [
"uvx",
"mcp-server-fetch",
"--compression-level", "high"
],
}
}
}
Use Cases
- Large Toolsets: When your MCP server exposes dozens or hundreds of tools
- Token-Limited Models: Maximize available context window for actual conversation
- Cost Optimization: Reduce token costs for pay-per-token API usage
- Performance: Faster initial responses with smaller context
- Multi-Server Setups: Use with multiple MCP servers without overwhelming the context
Command-Line Reference
Usage: mcp-compressor [OPTIONS] COMMAND_OR_URL
Run the MCP Compressor proxy server.
This is the main entry point for the CLI application. It connects to an MCP
server (via stdio, HTTP, or SSE) and wraps it with a compressed tool
interface.
Arguments:
COMMAND_OR_URL The URL of the MCP server to connect to for streamable HTTP
or SSE servers, or the command and arguments to run for
stdio servers. Example: uvx mcp-server-fetch \[required]
Options:
--cwd TEXT The working directory to use when running
stdio MCP servers.
-e, --env TEXT Environment variables to set when running
stdio MCP servers, in the form
VAR_NAME=VALUE. Can be used multiple times.
Supports environment variable expansion with
${VAR_NAME} syntax.
-H, --header TEXT Headers to use for remote (HTTP/SSE) MCP
server connections, in the form Header-
Name=Header-Value. Can be use multiple
times. Supports environment variable
expansion with ${VAR_NAME} syntax.
-t, --timeout FLOAT The timeout in seconds for connecting to the
MCP server and making requests. \[default:
10.0]
-c, --compression-level [max|high|medium|low]
The level of compression to apply to tool
the tools descriptions of the wrapped MCP
server. \[default: medium]
-n, --server-name TEXT Optional custom name to prefix the wrapper
tool names (get_tool_schema, invoke_tool,
list_tools). The name will be sanitized to
conform to MCP tool name specifications
(only A-Z, a-z, 0-9, _, -, .).
-l, --log-level [debug|info|warning|error|critical]
The logging level. Used for both the MCP
Compressor server and the underlying MCP
server if it is a stdio server. \[default:
WARNING]
--install-completion Install completion for the current shell.
--show-completion Show completion for the current shell, to
copy it or customize the installation.
--help Show this message and exit.