Discover all available database types and get the image ID required for creating a database.
MIT
606,627 tools. Updated 2026-09-24 10:13
"Creating a Memory Database for LLM Chat Conversations" matching MCP tools:
- Bulk-fetch recent LINE messages per chat and index them for cross-conversation search, backfilling missing vectors or reconciling selected conversations.MIT
- Check the health of the memory store: get memory count, encryption status, database location, and reflect availability.MIT
- Retrieve database tables and columns in an LLM-friendly format before writing SQL queries against an existing database.MIT
- Retrieve a list of AI chat conversations including titles, last message previews, models, and timestamps. Limit the number of results returned.MIT
- Execute SQL statements against a database using $1, $2 placeholders; results are sanitized for safe LLM context.MIT
Matching MCP Servers
- AlicenseNot gradedqualityAmaintenanceWraps Tool and ToolPackage instances from the llm-chat ecosystem behind the Model Context Protocol, enabling stdio and Streamable HTTP transports for MCP servers.13 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables agents to inspect configured LLM models and send chat requests to them, with support for parameter overrides, file-based prompts, and output to files.Apache 2.0
Matching MCP Connectors
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- Identify recent LINE conversations and obtain stable chat IDs for subsequent message retrieval. Use when the chat ID is unknown.MIT
- Summarize saved knowledge stored in your memory, broken down by surface (Chat, Code, Cowork) and type, along with database size and date range.MIT
- Get a list of supported database engine types, such as PostgreSQL, MySQL, and SQLite, to select the right engine when creating a new database connection in Superset.MIT
- Lists Microsoft Teams chat names and activity timestamps from the sidebar to help you browse conversations quickly.MIT
- Send a message in an ongoing LinkedIn chat conversation. Meant for existing chats with connections; for new chats, use the start chat tool.MIT
- Resume an AI session with saved project memory, restoring context and insights to maintain continuity across conversations.MIT
- List tables and views in a database schema, allowing you to select the correct table for creating a dataset.MIT
- Find past Telegram conversations by searching text keywords within a specific chat or supergroup. Locate relevant messages using chat ID, username, or phone number.Apache 2.0
- Detect installed local LLM provider folders to enable optional chat import from these sources.Apache 2.0
- List database schemas to select the right schema before querying tables or creating datasets.MIT
- Ingest text content into persistent memory with a source name. Store notes, decisions, or context for semantic retrieval across conversations.MIT
- List Zendesk Chat conversations with pagination. Use cursor, fields, and filter parameters to refine results.MIT
- Write a note to a shared directory, making it accessible across all conversations for cross-chat collaboration and persistent memory.MIT
- Retrieve recent Zendesk Chat conversations ordered by latest first, to review end-of-day transcripts or locate a specific chat by visitor name.MIT
- Preserve facts, decisions, and project context across conversations by creating durable markdown memories with structured metadata for easy retrieval.MIT