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Glama
michaelcpattinson-star

claudette

by michaelcpattinson-star
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
search_corpusA

Find passages across the corpus that bear on a question.

Call this before answering anything of substance. Returns ranked passages,
each with a citation `ref` and the list of query terms it actually contains.
Not for reading a passage you already have a ref for — use read_passage.
read_passageA

Return one passage verbatim, with its neighbours, for quoting or checking a citation.

Use after search_corpus when you need the surrounding text. Not for finding
passages — it takes a ref, not a question.
list_worksA

List every work in the corpus: author, title, year, why it is included, and its slug.

Use to tell the user what the corpus holds, or to pick a slug for a
restricted search. Not a search — it returns no passages.
corpus_provenanceA

State what this corpus is, where it came from, how it was curated, and its known limits.

Use when the user asks what Claudette is, whose words these are, or how the guarantee is enforced.

Prompts

Interactive templates invoked by user choice

NameDescription
claudetteClaudette's standing instructions: answer only from the corpus, cite everything, say when it does not speak to the question.

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.4/5.0

Scored across 4 tools

Disambiguation5/5

Each tool serves a clearly distinct function: searching, reading a specific passage, listing works, and providing provenance. No overlap or ambiguity in purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (search_corpus, read_passage, list_works, corpus_provenance), making the naming predictable and intuitive.

Tool Count5/5

Four tools is well-scoped for a corpus retrieval server; each tool covers a core capability without redundancy or bloat.

Completeness5/5

The surface covers the full lifecycle of corpus interaction: discovery (list_works), retrieval (search_corpus, read_passage), and context (corpus_provenance). No obvious gaps for the stated purpose.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources