OpenContext Context Management (Persistent Memory)

Give your AI assistant persistent memory. Stop repeating explanations, and build smarter.

When to use this skill

When you need to keep context across sessions
When you need to record project background/decisions
When you need to search prior conclusions/lessons
When you need knowledge sharing in a Multi-Agent workflow
When you want to reduce repetitive background explanations

1. Core concepts

Problem

When working with an AI assistant, context gets lost (across sessions, repos, and dates). You end up repeating background, re-explaining decisions, and sometimes the assistant continues with incorrect assumptions.

Solution

OpenContext is a lightweight personal context/knowledge store for AI assistants.

[Load context] → [Do work] → [Store conclusions]

Default paths

Item	Path
Contexts	`~/.opencontext/contexts`
Database	`~/.opencontext/opencontext.db`

2. Install and initialize

Install CLI

npm install -g @aicontextlab/cli
# Or use npx
npx @aicontextlab/cli <command>

Initialize (run inside the repo)

cd your-project
oc init

What oc init does:

Prepare the global context store (on first run)
Generate user-level commands/skills + mcp.json for the selected tool
Update the repo's AGENTS.md

3. Slash Commands

Beginner-friendly commands

Command	Purpose
`/opencontext-help`	When you don't know where to start
`/opencontext-context`	(Recommended default) Load background before work
`/opencontext-search`	Search existing documents
`/opencontext-create`	Create a new document/idea
`/opencontext-iterate`	Store conclusions and citations

Install locations

# Slash Commands
Cursor:      ~/.cursor/commands
Claude Code: ~/.claude/commands

# Skills
Cursor:      ~/.cursor/skills/opencontext-*/SKILL.md
Claude Code: ~/.claude/skills/opencontext-*/SKILL.md
Codex:       ~/.codex/skills/opencontext-*/SKILL.md

# MCP Config
Cursor:      ~/.cursor/mcp.json
Claude Code: ~/.claude/mcp.json

4. Core CLI commands

Folder/document management

# List folders
oc folder ls --all

# Create folder
oc folder create project-a -d "My project"

# Create document
oc doc create project-a design.md -d "Design doc"

# List documents
oc doc ls project-a

Search & manifest

# Search (keyword/hybrid/vector)
oc search "your query" --mode keyword --format json

# Generate a manifest (list of files the AI should read)
oc context manifest project-a --limit 10

Search modes

Mode	Description	Requirements
`--mode keyword`	Keyword-based search	No embeddings required
`--mode vector`	Vector search	Embeddings + index required
`--mode hybrid`	Hybrid (default)	Embeddings + index required

Embedding configuration (for semantic search)

# Set API key
oc config set EMBEDDING_API_KEY "<<your_key>>"

# (Optional) Set base URL
oc config set EMBEDDING_API_BASE "https://api.openai.com/v1"

# (Optional) Set model
oc config set EMBEDDING_MODEL "text-embedding-3-small"

# Build index
oc index build

5. MCP Tools

OpenContext MCP Tools

oc_list_folders    # List folders
oc_list_docs       # List documents
oc_manifest        # Generate manifest
oc_search          # Search documents
oc_create_doc      # Create document
oc_get_link        # Generate stable link

Multi-Agent integration

# Gemini: large-scale analysis
ask-gemini "Analyze the structure of the entire codebase"

# Codex: run commands
shell "docker-compose up -d"

# OpenContext: store results
oc doc create project-a conclusions.md -d "Analysis conclusions"

6. Multi-Agent workflow integration

Orchestration Pattern

[Claude] Plan
    ↓
[Gemini] Analysis/research + OpenContext search
    ↓
[Claude] Write code
    ↓
[Codex] Run/test
    ↓
[Claude] Synthesize results + store in OpenContext

Practical example: API design + implementation + testing

# 1. [Claude] Design API spec using the skill
/opencontext-context   # Load project background

# 2. [Gemini] Analyze a large codebase
ask-gemini "@src/ Analyze existing API patterns"

# 3. [Claude] Implement code based on the analysis
# (Use context loaded from OpenContext)

# 4. [Codex] Test and build
shell "npm test && npm run build"

# 5. [Claude] Create final report + store conclusions
/opencontext-iterate   # Store decisions and lessons learned

7. Recommended daily workflow

Before work (1 min)

/opencontext-context

Load project background + known pitfalls

During work

/opencontext-search

Search existing conclusions when unsure

After work (2 min)

/opencontext-iterate

Record decisions, pitfalls, and next steps

High-ROI document types

Acceptance Criteria - acceptance criteria
Common Pitfalls - common pitfalls
API Contracts - API contracts
Dependency Versions - dependency versions

8. Stable links (Stable Links)

Keep links stable across renames/moves by referencing document IDs:

[label](oc://doc/<stable_id>)

Generate a link via CLI

oc doc link <doc_path>

Generate a link via MCP

oc_get_link doc_path="Product/api-spec"

9. Desktop App & Web UI

Desktop App (recommended)

Manage/search/edit context with a native UI
Use without the CLI
Automatic index builds (in the background)

Citation features:

Action	How	Result
Cite text snippet	Select text → right-click → "Copy Citation"	Agent reads the snippet + source
Cite document	Click the citation icon next to the document title	Agent reads the full document + obtains stable_id
Cite folder	Right-click folder → "Copy Folder Citation"	Agent bulk-reads all docs in the folder

Web UI

oc ui
# Default URL: http://127.0.0.1:4321

Quick Reference

Essential workflow

Before: /opencontext-context (load background)
During: /opencontext-search (search)
After: /opencontext-iterate (store)

Core CLI commands

oc init              # Initialize project
oc folder ls --all   # List folders
oc doc ls <folder>   # List documents
oc search "query"    # Search
oc doc create ...    # Create document

MCP Tools

oc_list_folders  list folders
oc_list_docs     list documents
oc_search        search
oc_manifest      manifest
oc_create_doc    create document
oc_get_link      generate link

Paths

~/.opencontext/contexts      context store
~/.opencontext/opencontext.db  database

opencontext