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Hydra DB Server

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Provides tools for storing, searching, and managing memories with knowledge-graph enriched context via Hydra DB's agentic memory.

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Описание

Provides tools for storing, searching, and managing memories with knowledge-graph enriched context via Hydra DB's agentic memory.

README

MCP (Model Context Protocol) server for Hydra DB, the state-of-the-art agentic memory. Provides tools for storing, recalling, and managing memories with knowledge-graph enriched context.

Available Tools

hydra_db_search

Search through Hydra DB memories. Returns relevant chunks with graph-enriched context including entity paths and knowledge graph relations.

Parameter Type Required Description
query string Yes The search query to find relevant memories
max_results number No Maximum number of memory chunks to return (1-50, default: 10)
mode string No Recall mode: fast for quick semantic search, thinking for deeper personalised recall with graph traversal (default: thinking)
graph_context boolean No Whether to include knowledge graph relations in results (default: true)

hydra_db_store

Save important information to Hydra DB memory. Hydra DB automatically extracts insights, preferences, and builds a knowledge graph from the stored content. Supports plain text and markdown.

Parameter Type Required Description
text string Yes The information to store in memory
title string No Title for the memory entry (default: MCP Memory)
source_id string No Source identifier to group related memories together (e.g. session ID)
infer boolean No Whether Hydra DB should extract insights and build knowledge graph (default: true)
is_markdown boolean No Whether the text is in markdown format (default: false)

hydra_db_ingest_conversation

Ingest user-assistant conversation turns into Hydra DB memory. Hydra DB extracts insights, preferences, and knowledge graph entities from the conversation.

Parameter Type Required Description
turns array Yes Array of conversation turns, each with a user and assistant field
source_id string Yes Source identifier to group all turns from the same session together
user_name string No Name of the user for personalisation (default: User)

hydra_db_list_memories

List all stored user memories in Hydra DB. Returns memory IDs and their content. No parameters required.

hydra_db_delete_memory

Delete a specific user memory from Hydra DB by its memory ID. This action is irreversible.

Parameter Type Required Description
memory_id string Yes The ID of the memory to delete

hydra_db_fetch_content

Fetch the full content of a specific source by its source ID.

Parameter Type Required Description
source_id string Yes The source ID to fetch content for
mode string No Fetch mode: content for text, url for presigned URL, both for both (default: content)

hydra_db_list_sources

List all ingested sources in Hydra DB memory. Returns source IDs, titles, types, and metadata.

Parameter Type Required Description
source_ids array No Array of specific source IDs to filter by. If omitted, lists all sources

Configuration

Get Your Credentials

  1. Get your Hydra DB API Key from Hydra DB
  2. Get your Tenant ID from the Hydra DB dashboard

Environment Variables

Variable Description Default
HYDRA_DB_API_KEY Your Hydra DB API key Required
HYDRA_DB_TENANT_ID Your Hydra DB tenant identifier Required
HYDRA_DB_SUB_TENANT_ID Sub-tenant for data partitioning hydra-db-mcp
HYDRA_DB_LOG_LEVEL Log level: DEBUG, INFO, WARN, ERROR ERROR

Claude Desktop

{
  "mcpServers": {
    "hydradb": {
      "command": "npx",
      "args": ["-y", "@hydradb/mcp@latest"],
      "env": {
        "HYDRA_DB_API_KEY": "your-api-key",
        "HYDRA_DB_TENANT_ID": "your-tenant-id"
      }
    }
  }
}

Cursor & Windsurf

Client Config File
Cursor ~/.cursor/mcp.json
Windsurf ~/.codeium/windsurf/mcp_config.json
{
  "mcpServers": {
    "hydradb": {
      "command": "npx",
      "args": ["-y", "@hydradb/mcp@latest"],
      "env": {
        "HYDRA_DB_API_KEY": "your-api-key",
        "HYDRA_DB_TENANT_ID": "your-tenant-id"
      }
    }
  }
}

VS Code

Add to .vscode/mcp.json:

{
  "servers": {
    "hydradb": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@hydradb/mcp@latest"],
      "env": {
        "HYDRA_DB_API_KEY": "your-api-key",
        "HYDRA_DB_TENANT_ID": "your-tenant-id"
      }
    }
  }
}

Custom Sub-Tenant

To partition data, set the HYDRA_DB_SUB_TENANT_ID environment variable:

{
  "mcpServers": {
    "hydradb": {
      "command": "npx",
      "args": ["-y", "@hydradb/mcp@latest"],
      "env": {
        "HYDRA_DB_API_KEY": "your-api-key",
        "HYDRA_DB_TENANT_ID": "your-tenant-id",
        "HYDRA_DB_SUB_TENANT_ID": "my-project"
      }
    }
  }
}

How It Works

  • hydra_db_search queries POST /recall/recall_preferences for relevant memories and returns graph-enriched context (entity paths, chunk relations, extra context). Supports fast and thinking recall modes.
  • hydra_db_store sends text to POST /memories/add_memory with configurable infer, upsert, is_markdown, title, and source_id options. Hydra DB extracts insights and builds a knowledge graph automatically.
  • hydra_db_ingest_conversation sends user-assistant pairs to POST /memories/add_memory as conversation turns, grouped by source_id.
  • hydra_db_list_memories queries POST /list/data (kind: memories) to browse stored memories.
  • hydra_db_list_sources queries POST /list/data (kind: knowledge) to browse ingested sources, with optional source_ids filter.
  • hydra_db_delete_memory calls DELETE /memories/delete_memory to remove a specific memory.
  • hydra_db_fetch_content calls POST /fetch/content to retrieve the original ingested content, with mode options (content, url, or both).

Development

npm ci
npm run build
HYDRA_DB_API_KEY=your-key HYDRA_DB_TENANT_ID=your-tenant npm start

For development with auto-reload:

HYDRA_DB_API_KEY=your-key HYDRA_DB_TENANT_ID=your-tenant npm run dev

Testing

# unit tests (mocked HTTP)
npm test

# live integration test against Hydra DB
RUN_LIVE_TESTS=true HYDRA_DB_API_KEY=your-key HYDRA_DB_TENANT_ID=your-tenant npm run test:integration

Troubleshooting

  • API Key Issues: Ensure HYDRA_DB_API_KEY is set correctly
  • Connection Errors: Check your internet connection and API key validity
  • Tool Not Found: Make sure the package is installed and the command path is correct
  • Debug Logging: Set HYDRA_DB_LOG_LEVEL=DEBUG for verbose output

Contributing / Developer Setup

Get up and running quickly with the bootstrap script:

git clone https://github.com/usecortex/hydradb-mcp.git
cd hydradb-mcp
make bootstrap

This will install dependencies, build the project, and create a .env file from .env.example. Edit .env with your HydraDB credentials, then:

make dev          # Start MCP server in dev mode (auto-reload)
make test         # Run unit tests
make test-all     # Run unit + integration tests
make check-types  # Type-check without emitting

Run make help to see all available targets.

from github.com/usecortex/hydradb-mcp

Установить Hydra DB Server в Claude Desktop, Claude Code, Cursor

Рекомендуется · одна команда, все IDE
unyly install hydra-db-mcp-server

Ставит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.

Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh

Или настроить вручную

Выполни в терминале:

claude mcp add hydra-db-mcp-server -- npx -y @hydradb/mcp

FAQ

Hydra DB Server MCP бесплатный?

Да, Hydra DB Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Hydra DB Server?

Нет, Hydra DB Server работает без API-ключей и переменных окружения.

Hydra DB Server — hosted или self-hosted?

Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.

Как установить Hydra DB Server в Claude Desktop, Claude Code или Cursor?

Открой Hydra DB Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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