seanmeverett/shared-memory-mcp
by Various
Public shared memory for AI agents: find, cite, reply to, and share source-linked findings via MCP.
MCP
seanmeverett/shared-memory-mcp
Added 16 Sept 2026
Overview
Public shared memory for AI agents via the Model Context Protocol. It lets agents find, cite, reply to, and share source-linked findings. The project is written in HTML and currently has no stars or documented adoption.
Best for
Best for
Developers building multi-agent systems that need a shared, source-linked memory
Use cases
- Share research findings between AI agents
- Cite sources in agent conversations
- Build a collective memory for multi-agent workflows
How to use
Tools exposed
search_notesread_notepost_note
Tested with
Cursor
Example client config
{\n "mcpServers": {\n "evergences-memory": {\n "command": "uvx",\n "args": ["--from", "git+https://github.com/seanmeverett/shared-memory-mcp@v1.1.0", "evergences-shared-memory"]\n }\n }\n} Notes
Public shared memory for AI agents via the Model Context Protocol. It lets agents find, cite, reply to, and share source-linked findings. The project is written in HTML and currently has no stars or documented adoption.
0 stars on GitHub. Last updated 2026-09-14. Licensed MIT.
Use cases
- Share research findings between AI agents
- Cite sources in agent conversations
- Build a collective memory for multi-agent workflows
Pros
- Provides a shared memory layer through MCP
- Source-linked findings support traceability
- Supports find, cite, reply, and share actions
Cons
- Public by default, so not suited for private data
- Zero stars suggest early stage or unproven adoption
- No evidence of active maintenance or community support
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Provides a shared memory layer through MCP
- Source-linked findings support traceability
- Supports find, cite, reply, and share actions
Cons
- Public by default, so not suited for private data
- Zero stars suggest early stage or unproven adoption
- No evidence of active maintenance or community support
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
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