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Glama
git-fabric

@git-fabric/chat

Official
by git-fabric

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
QDRANT_URLYesQdrant Cloud cluster URL
GITHUB_TOKENYesGitHub PAT for state repo read/write
OPENAI_API_KEYYesOpenAI API key for text-embedding-3-small
QDRANT_API_KEYYesQdrant Cloud API key
ANTHROPIC_API_KEYYesAnthropic API key for Claude completions
GITHUB_STATE_REPONoState repo (default: ry-ops/git-steer-state)ry-ops/git-steer-state

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
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
chat_session_createA

Create a new chat session with Claude. Optionally set a system prompt, project tag, model, and title. Returns the sessionId to use in subsequent calls.

chat_session_listA

List recent chat sessions. Filter by project, state, and limit. Sessions are sorted by most recently updated first.

chat_session_getA

Get full session details including message history. Use this to inspect or resume a prior conversation.

chat_session_archiveA

Archive a session. Archived sessions are hidden from the default list but remain searchable and resumable.

chat_session_deleteA

Permanently delete a session and all its messages. This also removes vectors from Qdrant. Irreversible.

chat_message_sendA

Send a message in an existing session and get a Claude response. Reconstructs full conversation history for the API call. Stores both user message and assistant response. Returns the assistant reply with token usage.

chat_message_listB

List messages in a session with pagination. Returns messages in chronological order.

chat_searchA

Semantic search over all stored conversation content using vector similarity. Finds messages relevant to the query even if exact words don't match. Optionally scope to a project or specific session.

chat_context_injectA

Inject external context into a session before the next message send. Use this to pipe in Aiana memory recall, documentation snippets, or runtime state. The injected content is stored as a message and included in the next completion call.

chat_statusA

Return aggregate stats: total sessions, total messages, and tokens consumed today. Useful for quota monitoring and observability.

chat_healthA

Ping Anthropic and Qdrant services. Returns latency for each. Use to verify the app is operational before sending messages.

chat_thread_forkA

Fork a session at a specific message to explore an alternative branch of conversation. Creates a new session with all history up to and including the fork point. The original session is unchanged.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.1/5.0

Scored across 12 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no significant overlap. For example, chat_message_send handles sending messages, chat_search performs semantic searches, and chat_session_archive manages archiving, all targeting different actions and resources. The descriptions reinforce these distinctions, making tool selection straightforward for an agent.

Naming Consistency5/5

All tool names follow a consistent 'chat_' prefix with descriptive verb_noun patterns, such as chat_session_create, chat_message_list, and chat_thread_fork. This uniformity enhances readability and predictability, allowing agents to easily infer functionality from the names without confusion.

Tool Count5/5

With 12 tools, the server is well-scoped for managing chat sessions, messages, and related operations. Each tool serves a specific role, from creation and listing to archiving and forking, providing comprehensive coverage without unnecessary bloat. This count aligns perfectly with the domain's complexity.

Completeness5/5

The toolset offers complete CRUD and lifecycle coverage for chat sessions and messages, including create, list, get, update (via send), archive, and delete operations. Additional tools like search, health checks, and forking address advanced needs, leaving no obvious gaps for typical agent workflows in this domain.