Explain how agentmemory stores and retrieves coding agents’ memories, including its engine, search methods, memory lifecycle, ports, and web viewer. Useful for understanding the system or planning extensions to its functions.
How agentmemory is built, the iii engine primitives it runs on, its storage model, ports, and the viewer. Use when reasoning about how memory is stored or retrieved end to end, when extending the system, or when answering how agentmemory works under the hood.
Review the instructions the agent will receive before you install.
agentmemory is a memory server for coding agents. It runs locally, captures observations, indexes them for hybrid retrieval, and serves them back over REST and MCP. It is built on the iii engine.
Everything is a function, a trigger, or worker state on the iii engine. There is no separate plugin system; the worker registers functions (mem::*) and HTTP triggers (api::*) and the engine routes calls. agentmemory does not bypass iii; new capability is a new function plus a trigger.
Recall combines BM25 keyword search with configured vector similarity and graph expansion. A clean installation without an embedding provider uses BM25 without an API key. Set EMBEDDING_PROVIDER=local to enable on-device embeddings, which may download a model, or configure a remote provider. LLM compression and summaries require a configured provider and their relevant options.
Memories carry content, concepts, files, importance, and timestamps, grouped into sessions and optionally linked to commits. A lifecycle of capture, compress, consolidate, and forget keeps the store useful over time rather than letting it grow unbounded.
REST is the anchor at 3111. Streams = N+1 (3112), viewer = N+2 (3113), engine = N+46023 (49134). --instance N shifts the whole block by N*100.
A real-time web viewer at http://localhost:3113 shows memory building as sessions run. Useful for demos and for confirming capture is working.
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Connect agentmemory to coding agents such as Claude Code and Codex while preserving existing server settings. It guides configuration, host restarts, and checks that memory tools are available and can save and retrieve information.
Set up and troubleshoot a local agentmemory server by checking MCP connections, authentication, ports, and environment settings. Understand which optional memory features require additional configuration, model downloads, or token usage before enabling them.
Understand how agentmemory automatically records tool activity, prompts, and session boundaries through hooks, actions triggered by session events. Use it to check integration setup, investigate missing records, and distinguish capture from optional summaries and context injection.
Helps agents choose the right agentmemory tool through MCP, a protocol for connecting agents to tools. It explains tool roles and points to parameter references for saving, retrieving, organizing, and maintaining stored knowledge.
Guides HTTP integration with the agentmemory server for saving and searching knowledge. It explains authentication, request conventions, and endpoint references, including how to connect systems that do not support MCP, the agent tool connection protocol.
Trace a file, function, or line through Git history to the agent session linked to its commit. It presents recorded commit details, session summaries, and important observations to help explain the change.