The MCP Inception MCP Server allows you to delegate tasks and offload context windows using an agent-based LLM query system. It essentially acts as an agent for agents with three main capabilities:
- Execute MCP Client: Offload tasks to another AI for research purposes, fetching data without intermediate steps.
- Execute Parallel MCP Client: Run multiple AI tasks in parallel, returning responses as JSON key-value pairs.
- Execute Map-Reduce MCP Client: Process multiple items in parallel (map) and then sequentially combine the results (reduce) into a single output.
Disclaimer
Ok this is a difficult one. Will take some setting up unfortunately. However, if you manage to make this more straightforward, please send me PR's.
mcp-inception MCP Server
Call another mcp client from your mcp client. Delegate tasks, offload context windows. An agent for your agent!
This is a TypeScript-based MCP server that implements a simple LLM query system.
- MCP Server and Client in one
- Made with use of mcp-client-cli
- Offload context windows
- Delegate tasks
- Parallel and map-reduce execution of tasks
Features
Tools
execute_mcp_client
- Ask a question to a separate LLM, ignore all the intermediate steps it takes when querying it's tools, and return the output.- Takes question as required parameters
- Returns answer, ignoring all the intermediate context
- execute_parallel_mcp_client - Takes a list of inputs and a main prompt, and executes the prompt in parallel for each string in the input.
E.G. get the time of 6 major cities right now - London, Paris, Tokyo, Rio, New York, Sidney.
- takes main prompt "What is the time in this city?"
- takes list of inputs, London Paris etc
- runs the prompt in parallel for each input
- note: wait for this before using this feature
execute_map_reduce_mcp_client
- Process multiple items in parallel and then sequentially reduce the results to a single output.- Takes
mapPrompt
with{item}
placeholder for individual item processing - Takes
reducePrompt
with{accumulator}
and{result}
placeholders for combining results - Takes list of
items
to process - Optional
initialValue
for the accumulator - Processes items in parallel, then sequentially reduces results
- Example use case: Analyze multiple documents, then synthesize key insights from all documents into a summary
- Takes
Development
Dependencies:
- Install mcp-client-cli
- Also install the config file, and the mcp servers it needs in
~/.llm/config.json
- Also install the config file, and the mcp servers it needs in
- create a bash file somewhere that activates the venv and executes the
llm
executable
install package
Install dependencies:
Build the server:
For development with auto-rebuild:
Installation
To use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
The Inspector will provide a URL to access debugging tools in your browser.
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A TypeScript-based server that allows calling other MCP clients from your own MCP client, facilitating task delegation and context window offloading for enhanced multi-agent interactions.
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