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Glama
NalluriTanavreddy

slugline-mcp

by NalluriTanavreddy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
SLUGLINE_MCP_PERSIST_DIRNoDirectory where the Chroma persistent index is stored. Defaults to ~/.slugline-mcp/chroma if not set.~/.slugline-mcp/chroma

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
get_analysis_style

Return the tone/structure instructions the LLM should follow when analyzing a scene.

search_similar_scenes

Search the reference index for scenes similar to query.

Returns: A list of matches, ranked most similar first. Empty if the reference index isn't available (see get_retriever().unavailable_reason).

get_scene_details

Fetch full details for a specific reference scene.

Returns: A dict with the scene's movie, slugline, characters, and full text, or None if the id doesn't exist (or the index is unavailable).

list_indexed_movies

List every movie currently in the reference index.

Returns: A list of {"movie_name": ..., "imdb_id": ...} dicts, one per indexed movie. Empty if the reference index is unavailable.

find_mood_reference_scenesA

Find reference scenes that strongly achieve a target mood.

Returns: A dict with: - method: "tag_matched" if target_mood closely matched a precoded mood tag, "semantic_fallback" if it didn't and results came from raw nearest-neighbor search instead, or "unavailable" if the reference index isn't available. - matched_tag / tag_similarity: the closest precoded tag and its cosine similarity to target_mood, regardless of which method was used -- lets the caller judge match confidence even on the fallback path. - results: the ranked scene matches themselves. Empty if no scenes are available or the index is unavailable.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

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 1 tool

Disambiguation5/5

With only a single tool, there is no possibility of ambiguity. The tool's purpose is clearly distinct as the sole entry point.

Naming Consistency5/5

The sole tool uses a clear verb_noun pattern ('find_mood_reference_scenes'), and with only one tool, there are no inconsistencies to evaluate.

Tool Count3/5

A single tool is borderline appropriate for a server focused on mood reference scenes. It feels minimal but could be acceptable if the tool itself is comprehensive. However, most servers benefit from at least a few tools.

Completeness2/5

The server exposes only a query operation. There are no tools for adding, updating, or managing scenes or moods, which leaves significant gaps for any workflow beyond simple retrieval.

Maintenance

ActivitySlowing
ResponsivenessNo issues

Resources