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Persistent semantic memory API for AI agents via BlueColumn.
About
Persistent semantic memory API for AI agents via BlueColumn.
Security Report
9.0
Low Risk9.0Low RiskValid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. ⚠️ Package registry links to a different repository than scanned source. Imported from the Official MCP Registry.
14 files analyzed · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
What You'll Need
Set these up before or after installing:
Your BlueColumn API key. Get a free key at https://bluecolumn.aiRequired
Environment variable: BLUECOLUMN_API_KEY
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-bluecolumnconsulting-lgtm-bluecolumn-memory": {
"env": {
"BLUECOLUMN_API_KEY": "your-bluecolumn-api-key-here"
},
"args": [
"-y",
"bluecolumn-mcp"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
bluecolumn-mcp
MCP server for BlueColumn — persistent semantic memory for AI agents.
Give any MCP-compatible agent (Claude Desktop, LangChain, AutoGen, CrewAI) the ability to remember, recall, and store observations across sessions.
Tools
| Tool | Description |
|---|---|
remember | Ingest text, audio, or documents into persistent memory |
recall | Query memory with natural language, get AI-synthesized answer + sources |
note | Store lightweight agent observations as searchable vectors |
Setup
1. Get your BlueColumn API key
Sign up free at bluecolumn.ai — 60 min audio + 100 queries/month, no credit card required.
2. Install
npm install -g bluecolumn-mcp
3. Configure Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"bluecolumn": {
"command": "bluecolumn-mcp",
"env": {
"BLUECOLUMN_API_KEY": "bc_live_YOUR_KEY"
}
}
}
}
Restart Claude Desktop. Your agent now has persistent memory.
Usage
Once configured, your agent can:
Remember this: our API uses Voyage AI embeddings at 512 dimensions
→ Uses the `remember` tool automatically
What embedding model does our API use?
→ Uses the `recall` tool to query memory
Note: user prefers bullet points over paragraphs
→ Uses the `note` tool for quick observations
Example with LangChain
from langchain_mcp import MCPToolkit
toolkit = MCPToolkit(server_name="bluecolumn")
tools = toolkit.get_tools()
# Tools: remember, recall, note — all backed by BlueColumn
Pricing
| Plan | Price | Audio | Queries |
|---|---|---|---|
| Free | $0 | 60 min/mo | 100/mo |
| Developer | $29/mo | 600 min | 2,000 |
| Builder | $79/mo | 2,000 min | 8,000 |
| Scale | $249/mo | 6,000 min | 20,000 |
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