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/
- TypeScript docs (GH Pages): https://atlassian-labs.github.io/mcp-compressor/typescript/
- TypeScript package code: https://github.com/atlassian-labs/mcp-compressor/blob/main/typescript/
- Blog https://www.atlassian.com/blog/developer/mcp-compression-preventing-tool-bloat-in-ai-agents/
Added a sibling TypeScript implementation with matching compression concepts, OAuth support, in-process runtime APIs, and TypeScript CLI mode.
COMMAND_OR_URLcan now be a single MCP config JSON string. For now,mcpServersmust contain exactly one server, and its key becomes the default--server-nameunless one is passed explicitly.
--cli-mode— Converts any wrapped MCP server into a local CLI. Generates an executable shell script (Unix) or.cmdfile (Windows) so agents and users can interact with the backend via familiar command-line conventions rather than structured tool calls.
--toonify— Automatically converts JSON responses from wrapped backend tools into TOON format, a compact human- and LLM-readable alternative to JSON.
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.
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
- Python + TypeScript implementations: A mature Python implementation plus a sibling TypeScript package for Node.js consumers
- 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)
- TOON Output Conversion: Optionally convert JSON backend tool results to TOON with
--toonify - CLI Mode: Convert any MCP server into a local CLI with
--cli-mode— generates a shell script that lets you (or an AI agent) interact with the backend via familiar command-line syntax - Zero Functionality Loss: All tools remain fully accessible through the wrapper interface
- Easy Integration: Drop-in replacement for existing MCP servers
| Capability | Python | TypeScript |
|---|---|---|
| Core compression proxy server | ✅ | ✅ |
| stdio / streamable HTTP / SSE backends | ✅ | ✅ |
| Single-server MCP config JSON string input | ✅ | ✅ |
| Persistent OAuth support | ✅ | ✅ |
| CLI mode | ✅ mature | ✅ available |
| In-process runtime API for app/agent embedding | ✅ first-class | |
| Prompt/resource passthrough parity | ✅ broader | |
| Production maturity | ✅ primary implementation |
Use the Python implementation when you want the most mature feature set today. Use the TypeScript implementation when you want Node.js-native usage, in-process embedding, or tighter TypeScript ecosystem integration.
Install using pip or uv:
pip install mcp-compressor
# or
uv pip install mcp-compressorWrap 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/sseSee uvx mcp-compressor --help for detailed documentation on available arguments.
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 maxIf you want the wrapped backend to behave like a local command-line tool, start here:
mcp-compressor --cli-mode --server-name atlassian -- https://mcp.atlassian.com/v1/mcpThen use the generated CLI script:
atlassian --helpInstead of exposing the wrapped backend as many MCP tools, --cli-mode turns the backend into a local CLI with a single help tool for discovery.
This is especially useful when you want an agent to work through a shell-style interface, or when a backend server already makes more sense as commands and flags than as direct MCP tool calls.
flowchart LR
Client["MCP Client / Agent"] -->|discovers| HelpTool["<server_name>_help"]
HelpTool -->|explains commands| GeneratedCLI["Generated local CLI script\n(e.g. atlassian)"]
User["User or Agent"] -->|runs CLI subcommands| GeneratedCLI
GeneratedCLI --> Bridge["Local HTTP bridge\n127.0.0.1:<port>"]
Bridge --> Compressor["mcp-compressor\n--cli-mode"]
Compressor --> Backend["Wrapped MCP server"]
Backend --> Compressor
Compressor --> Bridge
Bridge --> GeneratedCLI
- One tool instead of many: the MCP client sees a single
<server_name>_helptool instead of the wrapper toolset - Natural shell UX: backend tools become CLI subcommands with flags derived from JSON schema
- Works well for agents: agents can inspect help, then call a local command repeatedly without carrying the full MCP tool surface in context
- OAuth still works: if the wrapped backend requires OAuth, CLI mode performs that connection flow before generating the local CLI
- TOON by default:
--toonifyis automatically enabled in CLI mode for compact, readable output
# Wrap a remote MCP server as a local CLI
uvx mcp-compressor --cli-mode --server-name atlassian -- https://mcp.atlassian.com/v1/mcp
# Or pass a single MCP config JSON string
uvx mcp-compressor --cli-mode '{"mcpServers": {"atlassian": {"url": "https://mcp.atlassian.com/v1/mcp"}}}'When CLI mode starts, it:
- Connects to the wrapped backend server, including OAuth if required
- Starts a local HTTP bridge on
127.0.0.1:<port> - Generates an executable script — on Unix this is typically written to
~/.local/bin/<name>if available onPATH, otherwise to the current directory; on Windows it writes a.cmdlauncher to a suitable directory onPATH - Exposes a single MCP tool named
<server_name>_helpso the client can discover the generated CLI and its subcommands
Example usage after startup:
# Top-level help — lists all subcommands
atlassian --help
# Per-tool help — shows flags derived from the backend tool schema
atlassian get-confluence-page --help
# Invoke a tool using ordinary CLI flags
atlassian get-confluence-page --cloud-id abc123 --page-id 456
# Escape hatch for complex inputs
atlassian create-jira-issue --json '{"cloudId":"abc","projectKey":"PROJ","summary":"Bug"}'CLI subcommand names are the snake_case → kebab-case conversion of backend tool names (for example getConfluencePage → get-confluence-page).
The generated script only works while mcp-compressor --cli-mode is running.
Use --cli-port if you want to pin the local bridge to a specific port.
# 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# 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 30When 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_toolUse --toonify to automatically convert JSON backend tool results into TOON format.
# Convert JSON backend tool results to TOON
mcp-compressor https://api.example.com/mcp --toonifyWhen --toonify is enabled:
- Successful backend tool results returned through direct tool calls are toonified if they are JSON objects or arrays
- Successful backend tool results returned through
invoke_tool(...)are also toonified - Wrapper responses from
get_tool_schema(...)andlist_tools(...)are never toonified - Wrapper-generated guidance or error text from
invoke_tool(...)is never toonified - Non-JSON text is returned unchanged
CLI mode is documented in the dedicated CLI Mode section above.
The short version: use --cli-mode, give the server a name, and interact with the generated local script while mcp-compressor is running.
mcp-compressor https://mcp.atlassian.com/v1/mcp --server-name atlassian --cli-mode --cli-port 8765# Set log level
mcp-compressor uvx mcp-server-fetch --log-level debug
mcp-compressor uvx mcp-server-fetch -l warningThe 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.
If --toonify is enabled, successful backend tool results are converted from JSON to TOON before being returned to the client. The wrapper helper responses themselves are not reformatted.
In CLI mode (--cli-mode), the compressor exposes a single <server_name>_help tool instead of the usual wrappers. All actual tool interaction happens through the generated shell script via a local HTTP bridge.
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
| 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.
You can also pass a single-server MCP config JSON string directly as COMMAND_OR_URL on the CLI. This is especially useful for remote servers when you want the config itself to carry the URL, headers, transport, or stdio command details.
For now, direct JSON-string input supports exactly one server entry in mcpServers.
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"
],
}
}
}- 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
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]
--toonify Convert JSON backend tool responses to TOON
format automatically.
--cli-mode Start in CLI mode: expose a single help MCP
tool, start a local HTTP bridge, and generate
a shell script for interacting with the
wrapped server via CLI. --toonify is
automatically enabled in this mode.
--cli-port INTEGER Port for the local CLI bridge HTTP server
(default: random free port).
--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.