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These integrations give agents built on a framework or agent runtime memory that lasts across runs: relevant context is recalled before each turn or task, and completed work is saved back to HydraDB. Each needs an API key and a database ID from the HydraDB dashboard.

Hermes

OpenClaw

CrewAI

LangChain

To use HydraDB from any other MCP client, connect the MCP server instead.

Hermes

HydraDB is a native Hermes Agent memory provider: relevant context is recalled before each turn and completed turns are persisted automatically. This is the proper, native way to make HydraDB Hermes’ long-term memory (alongside providers like supermemory, retaindb, and ham). It uses the HydraDB public API only (recall + knowledge ingest); no HydraDB SDK is required.
1

Install the provider

Requires Python 3.10+ and a Hermes Agent install.
2

Get credentials

3

Set environment variables

4

Enable it in config.yaml

Memory providers are single-select:

How it works

The integration implements Hermes’ MemoryProvider contract:
  • Auto-recall: Before each turn, Hermes calls prefetch, which queries HydraDB and returns graph-enriched context to inject into the request.
  • Auto-retain: After each turn, sync_turn persists the user/assistant exchange off-thread so the model is never blocked on a write.

MCP alternative

For pull-style recall (agent-invoked tools) instead of automatic memory, point Hermes at the HydraDB MCP server. The memory provider already gives automatic recall and retain, so MCP is optional.

OpenClaw

Automatically captures conversations, recalls relevant context with knowledge-graph connections, and injects it before every AI turn.
1

Install

Clone the repo and install from the local checkout:
Requires OpenClaw 2026.6.0 or later (openclaw --version).
2

Configure

Set credentials in the environment (or in the plugin config block plugins.entries.hydradb.config), then restart the gateway:
Optional: HYDRADB_COLLECTION (collection scope) and HYDRADB_BASE_URL. Turn capture reads conversation messages, which OpenClaw gates for non-bundled plugins; enable it with plugins.entries.hydradb.hooks.allowConversationAccess: true.
Lifecycle hooks: before_prompt_build recalls relevant memory and prepends it to the prompt, after_tool_call syncs edited files, agent_end captures the completed turn, and session_start syncs workspace docs. Manual actions come from the shipped skills: query, ingest, doctor, setup, and last-recall. Repo: hydradb-openclaw-plugin. OpenClaw runs on the same engine as the coding agent plugins, so its config keys and capture, search, and ingest modes match the config variables there.

CrewAI

HydraDB as external memory for CrewAI agents. Crews recall relevant history on each task and persist their outputs into HydraDB, so memory survives across runs.
Implements CrewAI’s Storage interface via ExternalMemory, available in CrewAI 1.0-1.10. On 1.11+ (which restructured memory around an embedding-based StorageBackend), use HydraDB over MCP instead. Outputs are stored as knowledge via the public /context/ingest path; search uses POST /query.
Repo: hydradb-crewai-plugin. Package: crewai-hydradb.

LangChain

HydraDB integration for LangChain: persistent, cross-session memory and retrieval for your chains and agents.
Requires langchain-core >= 0.3. Writes use the public knowledge path, so add_text/add_conversation store as knowledge; recall kind may be "memory", "knowledge", or "both". Ingestion is asynchronous, so recall a source only after it finishes indexing.
Repo: hydradb-langchain-plugin. Package: langchain-hydradb.

Source code