MCP SERVER

Configuration

The MCP server lets Claude Desktop, Cursor, Windsurf, Hermes Agent, OpenClaw and any MCP-compatible client use ChainMemory as a native tool.

Installation

Add this configuration to your claude_desktop_config.json:

JSON
{
  "mcpServers": {
    "chainmemory": {
      "command": "npx",
      "args": ["-y", "chainmemory-mcp"],
      "env": {
        "CHAINMEMORY_API_KEY": "your-api-key"
      }
    }
  }
}

Restart the client afterwards. Publishing a new version to npm does not update clients that are already running: the package is fetched when the client starts.

Available Tools

The current version exposes 34 tools. Reading is free; the operations that cost AIC are marked. See Costs for the full schedule.

Memory

Verification

Project State

Verifiable Role Contracts

Injection

Projects and identity

Autonomous Consolidation

Any AI client can consolidate the project state autonomously with update_project_state. This is the "client consolidates, chain verifies" architecture: the model proposes, the server validates and only then does it become state.

Operation grammar (29 ops)

Each operation has a type (op) and its own arguments. Use evidence_memory_ids — an array of memory numbers — to link supporting evidence; the server resolves the event hashes automatically.

Example

JSON — update_project_state call
{
  "project": "my-project",
  "ops": [
    {
      "op": "add_decision",
      "title": "Migrate to PostgreSQL",
      "statement": "SQLite cannot handle concurrent writes at current scale",
      "evidence_memory_ids": [142, 145]
    },
    {
      "op": "set_metric",
      "name": "db_migration_status",
      "value": "planning"
    },
    {
      "op": "add_milestone",
      "title": "PostgreSQL migration approved by team",
      "status": "done",
      "evidence_memory_ids": [145]
    }
  ],
  "consolidated_until_event": 150
}

Workflow

The typical MCP workflow:

Advanced Workflows

Claude Desktop — Architecture Sessions

Claude excels at high-level design. Use ChainMemory to preserve architectural decisions across sessions:

Prompt pattern — Claude Desktop
"Before we start, load my project state from ChainMemory.
Then let's design the authentication system.

After we decide, save the key decisions with tags 'architecture'
and 'auth'. Use importance 9 for anything that affects other
team members, and then propose the operations to consolidate
the state."

Claude reads the state with get_project_state, works with you on the design, saves decisions with chainmemory_remember, and proposes the consolidation with update_project_state. Next session, the auth architecture is already part of the state.

Cursor — Code with Memory

Cursor's MCP integration lets your coding AI remember why code was written a certain way. The configuration is the same as for Claude Desktop, in settings.json.

An effective workflow:

• Start of session — "Load the project state": decisions in force, open risks and priorities
• During coding — "Save: implemented webhook handler with retry logic, 3 attempts with exponential backoff"
• Bug fixes — "Save: fixed race condition in payment processing — the Stripe webhook was arriving before the DB transaction committed"
• End of session — "Consolidate what changed today", which proposes the operations and updates the state

Agentic Memory Pattern

The most powerful MCP pattern is agentic memory, where the AI manages its own knowledge:

System prompt for agentic memory
You have access to ChainMemory via MCP. Follow these rules:

1. At session start: call get_project_state to load the
   consolidated state of the project.
2. When you make a significant decision: save it with
   chainmemory_remember.
   - Include WHY you chose this approach
   - Tag it with the relevant domain
   - Importance 1-10: use 7 or more for decisions, 5 for
     observations
3. When you complete a milestone: save it and say what comes next.
4. When you identify a risk: save it with its severity.
5. At session end: propose the consolidation with
   update_project_state. Do not close or supersede existing
   items without the owner's approval: add in proposed state
   and let a human confirm.