How do I install the Cerebrun skill?

Run npx skillmds@latest add lord1egypt/cerebrun in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Cerebrun safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Cerebrun?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Cerebrun free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Cerebrun?

Lord1Egypt (@lord1egypt) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Cerebrun by lord1egypt — Agent Skill

Name: Cerebrun
Rating: 4.2 (5 reviews)
Author: Lord1Egypt

Cerebrun

MCP client for Cerebrun - comprehensive personal context and memory management system. Retrieve user context layers (language, projects, identity, vault), perform semantic search, manage knowledge base, and interact with LLM Gateway. Use when: (1) Retrieving user preferences or context, (2) Searching user's knowledge base, (3) Managing projects and goals, (4) Storing or querying personal information, (5) Accessing conversation history via LLM Gateway

Lord1Egypt Updated Sep 8, 2026 2 repo stars

File contents

Cerebrun MCP Client

Cerebrun (cereb.run) is a Model Context Protocol (MCP) server that provides persistent personal context management across sessions.

Quick Start

All requests require:

api_key: Cerebrun API key (Bearer token)
base_url: https://cereb.run/mcp

Context Layers

Layer 0 - Language, timezone, comms prefs Layer 1 - Projects, goals, pinned memories Layer 2 - Personal identity info, API and other keys Layer 3 - Encrypted vault (requires consent)

Usage

Get Context

curl -X POST
-H "Authorization: Bearer $API_KEY"
-H "Content-Type: application/json"
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_context","arguments":{"layer":0}}}'
https://cereb.run/mcp

Search Context

curl -X POST
-H "Authorization: Bearer $API_KEY"
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search_context","arguments":{"query":"Rust authentication","limit":5}}}'
https://cereb.run/mcp

Push Knowledge

curl -X POST
-H "Authorization: Bearer $API_KEY"
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"push_knowledge","arguments":{"content":"Important insight","category":"learning","tags":["rust","performance"]}}}'
https://cereb.run/mcp

Chat via Gateway

curl -X POST
-H "Authorization: Bearer $API_KEY"
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"chat_with_llm","arguments":{"message":"Hello","provider":"openai","model":"gpt-4"}}}'
https://cereb.run/mcp

Tools Reference

See REFERENCES.md for complete API documentation.

Script Usage

scripts/cerebrun.py get_context --layer 0 --api-key YOUR_KEY
scripts/cerebrun.py search_context --query "project" --api-key YOUR_KEY
scripts/cerebrun.py push_knowledge --content "New idea" --category "todo" --api-key YOUR_KEY

Configuration

Store API key in environment: CEREBRUN_API_KEY or pass via --api-key

---name: cerebrundescription: MCP client for Cerebrun - comprehensive personal context and memory management system. Retrieve user context layers (language, projects, identity, vault), perform semantic search, manage knowledge base, and interact with LLM Gateway. Use when: (1) Retrieving user preferences or context, (2) Searching user's knowledge base, (3) Managing projects and goals, (4) Storing or querying personal information, (5) Accessing conversation history via LLM Gateway---# Cerebrun MCP ClientCerebrun (cereb.run) is a Model Context Protocol (MCP) server that provides persistent personal context management across sessions.## Quick StartAll requests require:- `api_key`: Cerebrun API key (Bearer token)- `base_url`: https://cereb.run/mcp## Context Layers**Layer 0** - Language, timezone, comms prefs**Layer 1** - Projects, goals, pinned memories**Layer 2** - Personal identity info, API and other keys**Layer 3** - Encrypted vault (requires consent)## Usage### Get Contextcurl -X POST \ -H "Authorization: Bearer $API_KEY" \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_context","arguments":{"layer":0}}}' \ https://cereb.run/mcp### Search Contextcurl -X POST \ -H "Authorization: Bearer $API_KEY" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"search_context","arguments":{"query":"Rust authentication","limit":5}}}' \ https://cereb.run/mcp### Push Knowledgecurl -X POST \ -H "Authorization: Bearer $API_KEY" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"push_knowledge","arguments":{"content":"Important insight","category":"learning","tags":["rust","performance"]}}}' \ https://cereb.run/mcp### Chat via Gatewaycurl -X POST \ -H "Authorization: Bearer $API_KEY" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"chat_with_llm","arguments":{"message":"Hello","provider":"openai","model":"gpt-4"}}}' \ https://cereb.run/mcp## Tools ReferenceSee [REFERENCES.md](references/REFERENCES.md) for complete API documentation.## Script Usage```pythonscripts/cerebrun.py get_context --layer 0 --api-key YOUR_KEYscripts/cerebrun.py search_context --query "project" --api-key YOUR_KEYscripts/cerebrun.py push_knowledge --content "New idea" --category "todo" --api-key YOUR_KEY```## ConfigurationStore API key in environment: `CEREBRUN_API_KEY` or pass via `--api-key`

Frequently asked questions