memory_import_claude

Import Claude Code auto-memory files into AgentDB with ONNX vector embeddings. Reads ~/.claude/projects/*/memory/*.md files, parses YAML frontmatter, splits into sections, and stores with 384-dim embeddings for semantic search. Use allProjects=true to import from ALL Claude projects. Pass project...

Server Ruflo ruvnet/ruflo
Category Write
Risk class Medium
Parameters 00 required

What memory_import_claude does on Ruflo

AI agents use memory_import_claude to create or update resources in Ruflo — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ruflo environment.

Why memory_import_claude needs a policy

The primary function is to import and store data (Claude Code auto-memory files as embeddings) into AgentDB. While it begins by reading local files, the substantive action is persisting transformed data into a database. This is reversible (data can be updated/removed later), so it's Write rather than Destructive.

From the tool's definition Tool description explicitly states it 'reads...and stores with 384-dim embeddings' into AgentDB, which is a Write operation that creates/modifies data in the agent database.

Questions about memory_import_claude

What does the memory_import_claude tool do? +

Import Claude Code auto-memory files into AgentDB with ONNX vector embeddings. Reads ~/.claude/projects/*/memory/*.md files, parses YAML frontmatter, splits into sections, and stores with 384-dim embeddings for semantic search. Use allProjects=true to import from ALL Claude projects. Pass projectPath to override cwd-based detection (#1883 — required when Ruflo runs in WSL but Claude Code is on Windows). Pass excludeFilePatterns (glob list) or excludeFiles (absolute path list) to skip voice-load-bearing, PII, or persona-restricted files (#1937). Use when native Read/Write is wrong because you need (a) cross-session retrieval by semantic similarity (vector embeddings) not by file path, (b) namespacing across projects without managing directory layout, or (c) the .swarm/memory.db audit trail. For one-shot file I/O, native Read/Write is fine. It is categorised as a Write tool in the Ruflo MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on memory_import_claude? +

Register the Ruflo MCP server in PolicyLayer and add a rule for memory_import_claude: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Ruflo. Nothing to install.

What risk level is memory_import_claude? +

memory_import_claude is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit memory_import_claude? +

Yes. Add a rate_limit block to the memory_import_claude rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block memory_import_claude completely? +

Set action: deny in the PolicyLayer policy for memory_import_claude. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides memory_import_claude? +

memory_import_claude is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

// THE FULL RECORD

memory_import_claude is one line of Ruflo's registry record.

The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.

Teams ship this data inside their own products. See what a licence covers →

// GET IN TOUCH

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