Mercury MCP

Unclaimed

by norika1207-lab

Cross-architecture LLM internal observation database (23 models, 13 architecture families). Exposed as MCP tools for any AI coding agent.

Install

$pip install -e .

Unclaimed listing

Is this your MCP server?

This listing was auto-indexed from the public record. Claim it to edit the page, set compatibility and unlock growth tools. Takes under two minutes.

Claim this server

Tools (17)

codestral

22B (mistral coder variant)

command-r

35B (Cohere)

falcon3

gemma2

granite

3.1-dense-8B (IBM)

internlm2

llama

3.1-8B, 3.3-70B

mercury_about

Paper status, citations, contribution info

mercury_list_models

List all 23 observed models

mistral

7B-v0.3, small-3.2-24B

olmo2

7B (AllenAI fully-open)

phi3

medium-14B

qwen2

3B, 7B, 14B, 32B, coder-32B

starcoder2

15B

Tier-A

hooked into llamacpp.Llama.logitsprocessor to capture output-layer hot dims per token

Tier-B

transformers.AutoModelForCausalLM.frompretrained with outputhiddenstates=True, per-layer residual stream activation magnitudes binned into 10 quantiles

yi

1.5-9B