Memsolus MCP Server
Provides persistent long-term memory for AI agents through semantic search and automated knowledge graph extraction. It enables agents to store, recall, and reason over facts, preferences, and relationships across multiple conversations and sessions.
README
@memsolus/mcp
Persistent memory for AI agents. One line to install, zero config to remember everything.
Give your AI agents the ability to store, recall, and reason over long-term memory — preferences, facts, decisions, relationships, and structured knowledge — across conversations and sessions.
Built on the Model Context Protocol, works with Claude, GPT, and any MCP-compatible client.
Why Memsolus?
- Semantic search — Find memories by meaning, not just keywords. Hybrid search combines both for best results.
- Knowledge graph — Entities and relationships are automatically extracted. Ask "Who works on Project X?" and get structured answers.
- Auto-consolidation — Raw memories are processed into structured knowledge profiles, versioned and categorized.
- Memory pools — Shared memory spaces for teams and multi-agent collaboration.
- Priority-aware — Mark critical rules as HIGH priority. They rank higher in search and resist pruning.
- Multi-tenant — Isolate context per user, agent, or workspace. Fine-grained scoping built in.
Setup
Get your API key at app.memsolus.com/api-keys, then add the server to your tool:
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"memsolus": {
"command": "npx",
"args": ["-y", "@memsolus/mcp"],
"env": {
"MEMSOLUS_API_KEY": "mk_live_..."
}
}
}
}
Claude Code
claude mcp add memsolus -- npx -y @memsolus/mcp
Then set your key in .claude/settings.local.json:
{
"env": {
"MEMSOLUS_API_KEY": "mk_live_..."
}
}
Cursor
Add to .cursor/mcp.json in your project root:
{
"mcpServers": {
"memsolus": {
"command": "npx",
"args": ["-y", "@memsolus/mcp"],
"env": {
"MEMSOLUS_API_KEY": "mk_live_..."
}
}
}
}
Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"memsolus": {
"command": "npx",
"args": ["-y", "@memsolus/mcp"],
"env": {
"MEMSOLUS_API_KEY": "mk_live_..."
}
}
}
}
VS Code (Copilot)
Add to .vscode/mcp.json in your project:
{
"servers": {
"memsolus": {
"command": "npx",
"args": ["-y", "@memsolus/mcp"],
"env": {
"MEMSOLUS_API_KEY": "mk_live_..."
}
}
}
}
Zed
Add to Zed settings (Cmd+, > assistant > mcp):
{
"context_servers": {
"memsolus": {
"command": {
"path": "npx",
"args": ["-y", "@memsolus/mcp"],
"env": {
"MEMSOLUS_API_KEY": "mk_live_..."
}
}
}
}
}
Any MCP-compatible client
The server runs over stdio by default. Point your client to:
npx -y @memsolus/mcp
With the environment variable MEMSOLUS_API_KEY set.
What your agent can do
| Capability | Tools |
|---|---|
| Store & retrieve | add_memory, get_memory, get_memories, update_memory, delete_memory |
| Semantic search | search_memories — hybrid, semantic, or keyword mode |
| Knowledge profiles | get_knowledge — auto-compiled from memories, merged as Markdown |
| Shared pools | list_pools, add_memory_to_pool, search_pool |
| Knowledge graph | graph_search, graph_traverse, graph_query |
| Housekeeping | list_entities, delete_all_memories |
15 tools total. All exposed automatically via MCP.
Use Cases
- Personalized assistants — Remember user preferences, past decisions, and context across sessions
- Multi-agent systems — Shared memory pools let agents collaborate with common context
- Knowledge management — Auto-extract entities and relationships from unstructured text
- Customer support — Recall full interaction history and customer preferences instantly
- Research agents — Accumulate findings across sessions, search by concept
Self-Hosting
If you're running your own Memsolus API instance, use the MEMSOLUS_API_URL variable to point to it:
{
"mcpServers": {
"memsolus": {
"command": "npx",
"args": ["-y", "@memsolus/mcp"],
"env": {
"MEMSOLUS_API_KEY": "mk_live_...",
"MEMSOLUS_API_URL": "https://your-instance.example.com"
}
}
}
}
Programmatic Usage
import { createServer } from '@memsolus/mcp';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
const server = createServer({
baseUrl: 'https://api.memsolus.com',
apiKey: process.env.MEMSOLUS_API_KEY,
});
const transport = new StdioServerTransport();
await server.connect(transport);
Configuration
| Variable | Required | Default | Description |
|---|---|---|---|
MEMSOLUS_API_KEY |
Yes | — | Your API key (get one) |
MEMSOLUS_API_URL |
No | https://api.memsolus.com |
API base URL (for self-hosting) |
Links
License
MIT
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