# Cognio

> Use this tool when you need to retain long-term context and enable semantic search across conversations in AI assistants. Cognio solves the problem of information loss between interactions, allowing for more informed and personalized responses. It takes in conversation data via MCP and outputs relevant information, making it ideal for use cases requiring persistent memory and context-aware dialogue management.

Canonical page: https://skillsregistry.net/skills/0xrelogic-cognio  
JSON: https://api.skillsregistry.net/v1/skills/0xrelogic-cognio

## Description

Persistent semantic memory server for AI assistants via MCP, enabling long-term context retention and semantic search across conversations.

## Trust

- **Trust score (0–1):** 0.18
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/vuq9p9l1qk)
- **Repository:** <https://github.com/0xReLogic/Cognio>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "0xrelogic-cognio"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/0xrelogic-cognio` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/0xrelogic-cognio/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt