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Domain Memory Agent

Community

An MCP server for domain-specific knowledge management with semantic search and summarization.

GitHub source repository ↗

★ 2.7k Stars Category · Other Very popular Source revision 3277af5249f0

28FMRS · D

Reliability

4/20

Security and permissions

5/20

Maintenance

12/20

Documentation

3/20

Setup experience

4/20

Evidence is limited to the server manifest and a one-line marketplace description. This profile confirms the name, version, npm package identifier, stdio transport, repository-level MIT license, and the TF-IDF/extractive-summarization positioning. Tool names, client compatibility, permissions, and security details are not documented in the sources, so those fields are left empty rather than guessed.

Read the FMRS scoring method →

The Domain Memory Agent is an MCP server whose manifest describes domain-specific knowledge management with semantic search and summarization. It is listed in the jeremylongshore/claude-code-plugins-plus-skills repository under plugins/mcp/domain-memory-agent. The marketplace entry describes it as a knowledge base with TF-IDF semantic search and extractive summarization that requires no ML dependencies. The declared npm package is @claude-code-plugins-plus/domain-memory-agent version 1.0.0, using stdio transport. The repository is MIT-licensed, and this server is not maintained by the upstream product/protocol owner.

Tools

The tool list has not been reviewed yet.

Setup

The manifest declares the npm package @claude-code-plugins-plus/[email protected] with stdio transport, but it does not provide a server-specific install snippet. Repository-level README instructions show the general marketplace route: pnpm add -g @intentsolutionsio/ccpi followed by ccpi install <plugin>; alternatively, Claude Code's built-in command /plugin marketplace add jeremylongshore/claude-code-plugins. No standalone MCP client configuration JSON example is given in the supplied sources.

Fit and risk

Best for

MCP users who want a lightweight, dependency-light knowledge base.
Cases where TF-IDF retrieval and extractive summarization are sufficient.
Developers exploring non-official domain knowledge servers inside the Claude Code plugin marketplace ecosystem.

Not for

High-fidelity semantic search requiring vector/embedding retrieval or neural summarization.
Production knowledge platforms that need documented authentication, encryption, and access controls.
Users who need a complete tool catalog or official support commitments before installing.

Required permissions

The source does not document an explicit permission list.
Because transport is stdio, the server is launched as a local process by the MCP client; actual filesystem or network access depends on the npm package implementation, which is not described in the supplied manifest.

Risks and side effects

Unofficial third-party server; it is not maintained by Anthropic, Claude Code, or the upstream product/protocol owner.
Installing an npm package carries normal supply-chain integrity and dependency risks.
The manifest does not list concrete tool names, security model, or data-handling guarantees.
Storage, encryption, and retention of knowledge-base data are not described in the provided materials.

Troubleshooting

Before configuring, verify that package @claude-code-plugins-plus/[email protected] exists on npm with that version.
Ensure the MCP client can spawn stdio processes and that the runtime required by the npm package is available.
If the server does not appear, inspect MCP client logs for startup or transport errors.
If using the repository manifest, check that the path plugins/mcp/domain-memory-agent/server.json matches the client configuration.
If no tools show up, inspect the installed package's own documentation or source; the supplied materials do not list tool names.

Use cases

Maintaining a searchable knowledge base for a specific technical or business domain.

Retrieving relevant knowledge snippets using TF-IDF-based semantic search.

Producing extractive summaries from stored domain knowledge.

Adding knowledge-management capabilities without additional ML model dependencies.