Reexpress MCP Server
by ReexpressAI
Reexpress MCP Server adds state-of-the-art statistical verification to complex LLM pipelines. It provides a reliable, statistically robust AI second opinion for AI workflows, especially in software development and data science.
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What is Reexpress MCP Server?
Reexpress MCP Server is a drop-in solution that allows Claude 3.7 Sonnet to check its responses with a pre-trained Similarity-Distance-Magnitude (SDM) estimator, providing a robust estimate of predictive uncertainty. It enables reasoning with SDM verification, opening up new use-cases for LLMs and agents.
How to use Reexpress MCP Server?
Install the MCP server and add the Reexpress prompt to the end of your chat text. The server uses the SDM estimator to verify Claude's response. You can adapt the model by using ReexpressAddTrue or ReexpressAddFalse tools after a verification.
Key features of Reexpress MCP Server
State-of-the-art statistical verification for LLM pipelines
Similarity-Distance-Magnitude (SDM) estimator for uncertainty estimation
Adaptable model through ReexpressAddTrue/False tools
Reasoning with SDM verification
File access control via ReexpressDirectorySet() and ReexpressFileSet()
Local processing of SDM estimator on Apple silicon Macs
Use cases of Reexpress MCP Server
Software development
Data science
Search and QA
Refining LLM answers
Determining the need for external resources
Identifying impasses in LLM reasoning
FAQ from Reexpress MCP Server
How do I install the server?
How do I install the server?
See INSTALL.md for installation instructions.
What configuration options are available?
What configuration options are available?
See CONFIG.md for configuration details.
How do I use the server?
How do I use the server?
See documentation/HOW_TO_USE.md for usage instructions.
What are the guidelines for using the server?
What are the guidelines for using the server?
See documentation/GUIDELINES.md for guidelines.
Where can I find more information about the training and calibration data?
Where can I find more information about the training and calibration data?
See documentation/DATA.md for details on the training and calibration data.