Octopoda Memory MCP Server

@RyjoxTechnologies

Basic information

About Octopoda Memory MCP Server

Persistent memory for AI agents that survives across sessions. Store, recall, and semantically search memories. Includes loop detection that catches agents stuck repeating themselves, full audit trails, shared memory between agents, and a real-time dashboard. Works with Claude Co

#memory #agents #persistent-memory #semantic-search#loop-detection#audit-trail #langchain #crewai #openai-agents

Octopoda Memory MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "octopoda": {
      "command": "python",
      "args": [
        "-m",
        "synrix_runtime.api.mcp_server"
      ],
      "env": {
        "OCTOPODA_API_KEY": "your-key-from-octopodas.com"
      }
    }
  }
}

Octopoda Memory MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Octopoda Memory?

Octopoda Memory is a persistent memory system for AI agents. It allows agents to store, recall, and search memories that survive across sessions, restarts, crashes, and deployments. It is designed for developers building AI agents that need long-term memory, shared knowledge, and monitoring capabilities.

How to use Octopoda Memory?

Install the package with pip install octopoda, obtain a free API key from https://octopodas.com, then add it to Claude Code using the command: claude mcp add octopoda -s user -e OCTOPODA_API_KEY=your-key -- python -m synrix_runtime.api.mcp_server.

Key features of Octopoda Memory

Persistent memory that survives restarts, crashes, and deployments
Semantic search to find memories by meaning
Loop detection to catch agents repeating themselves
Audit trail logging every decision with reasoning
Shared memory for agents to share knowledge through memory spaces
Real-time dashboard to monitor all agents at localhost:7842

Use cases of Octopoda Memory

Storing agent memories that persist across multiple sessions
Searching for past memories by semantic similarity rather than exact keys
Preventing agents from burning tokens by repeating the same actions
Logging and reviewing agent decision rationale for debugging
Enabling multiple agents to share and access common knowledge

Frequently asked questions

What is Octopoda Memory?

Octopoda Memory provides persistent memory for AI agents, allowing them to store, recall, and search memories that survive across sessions.

How do I install Octopoda Memory?

Install it via pip: `pip install octopoda`. Then get a free API key at https://octopodas.com and add the server to Claude Code with the provided command.

What tools does Octopoda Memory provide?

It offers 13 tools including octopoda_remember, octopoda_recall, octopoda_recall_similar, octopoda_search, octopoda_recall_history, octopoda_snapshot, octopoda_restore, octopoda_share, octopoda_read_shared, octopoda_list_agents, octopoda_agent_stats, octopoda_log_decision, and octopoda_loop_status.

What is the real-time dashboard address?

The real-time dashboard runs at localhost:7842.

Where do I get an API key?

A free API key is available at https://octopodas.com.

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