Lists all imported chat sessions with name, platform, message count, and time range. Returns plain text by default (set format=json for JSON).

Gets full details of a single session by ID. Returns plain text by default (set format=json for JSON).

The primary tool for reading message content. Retrieves up to 500 messages per call with filters for keyword, time range, and sender. Use page to paginate. Returns plain text by default (set format=json for JSON, format=text for compact format). Always prefer this over execute_sql when reading messages.

Lists all members in a session with their platformId, name, and role. Returns plain text by default (set format=json for JSON).

Returns statistical overview of a session: message counts, active members, time distribution. Returns plain text by default (set format=json for JSON).

For statistical aggregation ONLY (COUNT, GROUP BY, SUM, AVG). Do NOT use to fetch message content — use get_messages for that. Max 200 rows returned. Available tables: message, member.

Get conversation in plain text format with filtering and compression. Returns compact text optimized for LLM context (saves tokens vs JSON).

Get full conversation across multiple pages, returns compact text format. Use for small to medium sessions only.

Get N messages before and after one or more specific message IDs. Use when the user references "what was being said around message X" or wants to see the conversation surrounding a specific message.

Get messages between two specific members (interleaved by time). Use when the user asks "what did A and B talk about". Members must be referenced by their numeric DB id; call get_members first to look them up.

Get AI-generated summaries of chat sub-sessions from the chat_session table. Use to quickly survey what topics have been discussed. Supports keyword filtering and time range. Returns text by default.

Full-text search messages via FTS5, then expand each hit with surrounding context messages. Use for "did anyone mention X" style queries where conversation context matters.

Get message count distribution bucketed by hour, weekday, or day. Use for "when are people most active" type questions. Timezone-aware bucketing.

Top members ranked by message count with percentage of total. Use for "who talks the most" or "most active members" type questions. Supports top_n and time filters.

Get the historical name changes (account name, nickname) for a single member. Useful for tracking identity changes over time.

Reply intervals between consecutive messages from different senders, grouped by (from, to) pair. Excludes same-sender continuations and gaps over 1 hour. Use for "who responds fastest" type questions.

Word/keyword frequency analysis. Currently not implemented in the MCP server due to NLP dependency size; returns a stub message with alternative approaches.