Meko MCP Server

MCP server and tools reference

The Meko MCP Server provides the primary tools for managing datapacks, conversations, memories, knowledge base search, and connecting to the PostgreSQL-compatible YugabyteDB database for executing database commands.

To connect from IDEs and MCP-compatible clients using your datapack URL and API key, see Quick start — Connect your AI client.

Tools

The Meko MCP Server provides the following tools.

Use	For
Conversation `conversation_*`	Full saved chat history and thread replay. Example: Save or retrieve this chat
Memory `memory_*`	Durable facts, preferences, decisions, and useful outcomes you want to recall across agents. Example: Remember this about me or the project
Knowledge base `knowledgebase_*`	Reusable, persistent, indexed shared documents, and collective memories that can be searched across agents. Example: Search this in the knowledge base
Database `db_*`	Structured operational data you want to query or modify with SQL. Example: Run SQL on my data
Datapack `datapack_*`	Provisioning and managing Meko workspaces/environments. Example: Create or manage a workspace

Conversation tools

Tool	Description
`conversation_create`	Create a stored conversation container for all conversations in a datapack. Use this to save a chat/thread, not just a fact or document. Typical inputs: `scope, agent_id, session_id, datapack_id, title, run_id, metadata`
`conversation_add_message`	Add a user/assistant turn to a stored conversation. Use this to preserve full exchanges rather than storing long-term facts. Typical inputs: `scope, seed, datapack_id, conversation_id, agent_id, input, output, reasoning, metadata`
`conversation_get`	Fetch a stored conversation, optionally with messages. Use this to review or replay a past conversation. Typical inputs: `scope, datapack_id, agent_id, conversation_id, include_messages, limit, offset`
`conversation_list`	List stored conversations. Use this to browse saved chat history. Typical inputs: `scope, datapack_id, agent_id, limit, offset`
`conversation_update`	Update a conversation title or metadata. Use this when organizing or relabeling stored conversations. Typical inputs: `scope, datapack_id, conversation_id, agent_id, title, metadata`
`conversation_delete`	Permanently delete a stored conversation. Use this to remove saved conversation history. Typical inputs: `scope, datapack_id, conversation_id, agent_id`

Memory tools

Tool	Description
`memory_add`	Store durable facts, preferences, decisions, or useful outcomes for a better context. Use this to add long-term reusable memory across threads. Typical inputs: `scope, datapack_id, agent_id, conversation_id, text, messages, run_id, metadata`
`memory_search`	Search stored memories semantically and return related graph relations. Use this to recall prior facts, preferences, or decisions. Typical inputs: `scope, datapack_id, agent_id, conversation_id, query, limit`
`memory_get_all`	List all memories for an agent or user scope. Use this to audit or inspect what's been remembered. Typical inputs: `scope, datapack_id, agent_id, conversation_id, run_id`
`memory_get_by_id`	Retrieve a single memory by ID. Use this to inspect a memory. Typical inputs: `scope, datapack_id, agent_id, conversation_id, memory_id`
`memory_update`	Replace the text of an existing memory. Use this to correct a remembered fact. Typical inputs: `scope, datapack_id, agent_id, conversation_id, memory_id, text`
`memory_delete_by_id`	Delete one memory. Use this to remove a specific stored memory. Typical inputs: `scope, datapack_id, agent_id, conversation_id, memory_id`
`memory_delete_all`	Delete all memories in a scope. Use this for a full reset or broad cleanup. Typical inputs: `scope, datapack_id, agent_id, conversation_id, run_id`

Knowledgebase tools

Tool	Description
`knowledgebase_search`	Perform a similarity search based on the user query. Use this when you want to search the knowledge base for your queries. Typical inputs: `scope, datapack_id, agent_id, conversation_id`

Database tools

Tool	Description
`db_run_read_only_query`	Run a read-only SQL query and return JSON results. Use this for direct structured data access using YSQL. Typical inputs: `scope, datapack_id, conversation_id, query`
`db_run_write_query`	Run a write SQL statement in a transaction. Use this to insert, update, or delete structured data. Typical inputs: `scope, datapack_id, conversation_id, query`
`db_summarize_database`	Summarize tables, schema, and row counts. Use this to explore a datapack's database before writing queries. Typical inputs: `scope, datapack_id, conversation_id, schema`

Datapack tools

Tool	Description
`datapack_create`	Provision a new datapack with database and MCP details. Use this to set up a new isolated Meko environment. Typical inputs: `scope, conversation_id, datapack_id, name`
`datapack_describe`	Return datapack details and optional status. Use this to inspect an existing datapack. Typical inputs: `scope, conversation_id, datapack_id, name, include_status`
`datapack_list`	List available datapacks. Use this to see all workspaces/environments. Typical inputs: `scope, conversation_id, datapack_id, name`
`datapack_update`	Update a datapack's database connection string. Use this to point a datapack to a new database connection. Typically used when you have access to multiple datpacks. Typical inputs: `scope, conversation_id, datapack_id, name, include_status, connection_string`
`datapack_delete`	Permanently delete a datapack. Use this to completely delete an environment. Typical inputs: `scope, conversation_id, datapack_id, name`