Practical overview
When it fits
Use it when an AI-agent system needs persistent, shared context across sessions or agents, especially when both REST and MCP access are useful.
Who it is for
- Developers building LangGraph, CrewAI or AutoGen agent pipelines
- Teams connecting multiple agents or sessions to shared memory
- Users of Claude Desktop, Claude Code or OpenCode who need persistent context
- Engineers seeking CLI, dashboard, REST and MCP access to one memory service
Documented uses
- Store agent decisions and project context for later sessions
- Share memory across agents and pipeline runs
- Retrieve context through REST endpoints or MCP
- Represent relationships between facts in a causal knowledge graph
- Maintain longer-term context through autonomous consolidation
Requirements & limits
The project is documented as open-source and provides REST and MCP access. The repository identifies an Apache-2.0 license and supports CLI, cloud, self-hosted and server deployment contexts.
- REST and MCP transports are both documented.
- The service includes CLI and dashboard access in addition to APIs.
- Agent-scoped retrieval can use the X-Agent-ID header and tag search.
- The project documents local ONNX embeddings.
- The implementation is Python-based and licensed under Apache-2.0.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Connect an agent pipeline through the REST API
Set up the documented HTTP service and use its memory endpoints for storage and retrieval.
Before you start
- Python package installation with pip
- An agent pipeline or HTTP client
- The mcp-memory-service package
Steps
Install the package with the command below.
pip install mcp-memory-serviceStart the HTTP service with
MCP_ALLOW_ANONYMOUS_ACCESS=true memory server --http.Send memory data to
POST /api/memories.Search stored context with
POST /api/searchor retrieve by tag withPOST /api/search/by-tag.Use
X-Agent-IDon a store request to tag memories for agent-scoped retrieval.
Expected outcome
An HTTP-accessible memory service with documented storage and search routes for agent pipelines.
Guide limitations
- The supplied documentation does not provide integration implementation details or test results.
- The anonymous-access setting shown in the quick start is part of the documented setup and should be evaluated for the deployment context.
Add MCP memory access to Claude Desktop
Install the service and configure Claude Desktop to use its local MCP server.
Before you start
- The mcp-memory-service package
- Claude Desktop
- Access to the Claude Desktop configuration file
Steps
Install the package with the command below.
pip install mcp-memory-serviceAdd the documented
memoryMCP server configuration to Claude Desktop's configuration file.Use the platform-specific configuration path for macOS, Windows or Linux.
Restart Claude Desktop.
Expected outcome
Claude Desktop is configured with the documented local memory MCP server.
Guide limitations
- The guide covers configuration and restart, but does not document a verification test or further memory workflow.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 1 October 2026
- Original website title
- doobidoo/mcp-memory-service · Official homepage title · retained in its source language

