Slowave MCP server

<!-- mcp-name: io.github.slowave-ai/slowave -->

Living memory layer across your coding agents and AI tools. Supports: Claude Code, Codex, OpenCode, Cursor, Cline, Windsurf/Devin Desktop, Claude Desktop

AI agents have large context windows, but that context ends with your current session. Open a new session, switch from Claude Code to Codex, and you have to restate the same decisions, constraints, and failed attempts. Slowave gives your agents one local, shared memory, without requiring a separate LLM for memory maintenance.

Slowave is designed as an adaptive memory layer rather than a static retrieval or summarisation system. It approaches agent memory from a different angle:

Memory and reasoning feed each other in a continuous loop.

graph LR
    LLM["Reasoning<br/>(Claude, Codex, etc.)"]
    MEM["Memory<br/>(Slowave)"]

    MEM -->|Retrieve| LLM
    LLM -->|Feedback| MEM
    MEM -->|Adapt| MEM

Agent memory is not only a retrieval problem. A useful memory system should retain what helps the agent achieving its goal, weaken what does not, and continuously adapt based on use. Slowave addresses this with a continuous feedback loop between your agent and its memory:

remember → recall → use → feedback → reinforce / weaken → decay

Slowave adapts the salience of stored memories based on your agent's feedback.

Over time, your agent’s feedback shapes what Slowave returns without needing a separate LLM judge inside the memory layer.

Memory becomes something continuously shaped by use rather than a static collection of facts waiting to be retrieved.

• Keep context across tasks: Your agents can reuse recorded decisions, preferences, constraints, and lessons instead of making you repeat them.
• Improves with use: Useful memories strengthen, irrelevant ones lose priority, stale knowledge can be suppressed or superseded.
• Learns from experience: Decisions, outcomes, and multi-step solutions can become reusable memories and procedures.
• Runs locally: Slowave stores memory in SQLite and does not send it to a hosted memory service.
• No LLM API key: The memory core performs maintenance and retrieval without LLM calls or an LLM API key.
• Inspectable: Review memories, retrievals, feedback, procedures, and system activity in the local dashboard.

The first useful payoff is simply not having to repeat the same constraint in the next task.

Over time, the way you work becomes reusable context for your agent.

See platform coverage and manual steps.

Installation

Quick start

pipx install slowave
slowave setup --dry-run
slowave setup

The quick start configures every detected client. To configure just one client at a time, see the installation reference.

[!IMPORTANT]

No LLM API key required.

To remove Slowave, see the removal guide.

What changes in your workflow?

Slowave is transparent to your work. You keep working with your agent as usual.

Slowave is strictly connected to your agent in both directions:

• Agent → Slowave: When your agent encounters a durable fact, decision, or procedure the installed lifecycle directs it to preserve that claim into Slowave.
• Slowave → Agent: At the beginning of each task Slowave may return a compact, scoped set of relevant recorded memories or procedures to your agent, so that it can act upon its own memories.

Shortened. The full README is on GitHub.