cognex 0.1.6

Your AI forgets everything. Cognex doesn't.

Cognex

Your AI forgets everything. Cognex doesn't.

Give your AI coding assistant persistent memory, decision tracking, trust management, and now — structured cognitive state that survives across sessions and agents.

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Why Use It?

You: "Remember I prefer pytest over unittest"

Next session:
AI: "Got it — I'll use pytest as we discussed."

Your AI forgets everything between sessions. Cognex fixes that — and in v0.1.6, it does it with full structured cognitive state tracking.

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What's New in v0.1.6

• Cognitive Units: First-class structured state with content, rationale, scope, and confidence
• Delta Tracking: Append-only change log per unit — full audit trail of how cognition evolved
• Staleness Scoring: Computed on read from override count, last verified age, and confidence
• Selective Retrieval: get_relevant_units() scores by BM25 + confidence + recency + scope match
• Cognitive Snapshot: export_snapshot() returns full structured CHP handoff bundle with delta trail
• 8 New MCP Tools: unit_commit, unit_checkout, unit_search, unit_mark_overridden, unit_verify, unit_get_relevant, unit_export_snapshot, unit_decay_stale
• TeleportBundle Enhancement: Now carries cognitive_units for full cross-machine cognitive state transfer
• CLI Fix: cognex --status now working (was reported done in 0.1.5 but not implemented until now)

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Features

Feature	What It Does
Persistent Memory	Remembers preferences, facts, patterns across sessions
Decision Ledger	Tracks choices made and their outcomes
Trust Engine	Learns which tools you approve vs deny
Teleportation	Export your cognitive state, load it on another machine — now Ed25519 signed
Pattern Intelligence	Discovers behavioral patterns from decision history
Swarm Mode	Turn natural language into multi-agent plans
MCP Prompts	5 built-in prompts for common workflows
Auto-Installer	One command setup for 7+ AI platforms

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Quick Install

Option A — Auto-installer (Recommended)

uvx cognex --install

Detects your AI tool (Claude Code, OpenCode, Cursor, VS Code, etc.) and writes the correct config automatically.

Option B — One command (Terminal)

Mac/Linux:

curl -fsSL https://raw.githubusercontent.com/Gaurav7974/cognex/main/install.sh | sh

Windows (PowerShell):

irm https://raw.githubusercontent.com/Gaurav7974/cognex/main/install.ps1 | iex

Option C — Paste this into your AI agent

Install and configure the cognex MCP server on my system.

Steps:
1. Run: pip install cognex
2. Detect which AI tool I am using (Claude Code / OpenCode / Cursor / Codex / VS Code)
3. Find the correct MCP config file for this tool
4. Add cognex to the config:
   - command: "cognex"
   - no extra args needed
5. Tell me to restart my AI tool
6. After I restart, call substrate_start_session with session_id "setup-verify" to confirm it works

Option D — Manual

See the Configuration section below.

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Check Your Status

New in v0.1.5 — inspect your memory bank without starting the server:

cognex --status

Output:

Cognex v0.1.5
─────────────────────────
Memories:       142
Decisions:       38
Trust records:   21
DB path:        .substrate/substrate.db

Configured tools:
  ✓ Claude Code
  ✓ OpenCode

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Supported AI Tools

Tool	Works?
Claude Code	✅
Claude Desktop	✅
OpenCode	✅
Cursor	✅
Codex	✅
VS Code (Copilot)	✅
Cline	✅
Windsurf	✅
Zed	✅
Any MCP-compatible tool	✅

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Installation

Option 1: uvx (Recommended — no install needed)

uvx cognex

Option 2: pipx (isolated environment)

pipx install cognex

Option 3: pip

pip install cognex

Option 4: From source

git clone https://github.com/Gaurav7974/cognex
cd cognex
pip install -e .

Verify

cognex --help
cognex --status

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Configuration by AI Tool

Claude Code

claude mcp add cognex -- uvx cognex

Or manually in ~/.claude.json or .mcp.json:

{
  "mcpServers": {
    "cognex": {
      "command": "uvx",
      "args": ["cognex"]
    }
  }
}

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Claude Desktop

Config file:

• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Mac: ~/Library/Application Support/Claude/claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "cognex": {
      "command": "uvx",
      "args": ["cognex"]
    }
  }
}

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OpenCode

Config file: ~/.config/opencode/opencode.json or opencode.json in project root

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "cognex": {
      "type": "local",
      "command": ["uvx", "cognex"],
      "enabled": true
    }
  }
}

Note: OpenCode uses "mcp" not "mcpServers", and requires "type": "local".

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Cursor

Config: ~/.cursor/mcp.json

{
  "mcpServers": {
    "cognex": {
      "command": "uvx",
      "args": ["cognex"]
    }
  }
}

Note: Cursor caps at 40 tools. Cognex uses 20, well within limit.

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VS Code (GitHub Copilot Agent Mode)

Config: .vscode/mcp.json in workspace, or Command Palette → MCP: Open User Configuration

{
  "servers": {
    "cognex": {
      "command": "uvx",
      "args": ["cognex"]
    }
  }
}

Note: VS Code uses "servers" not "mcpServers".

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Cline

Open Cline → MCP Servers → Configure tab → Edit Config:

{
  "mcpServers": {
    "cognex": {
      "command": "uvx",
      "args": ["cognex"],
      "disabled": false,
      "alwaysAllow": []
    }
  }
}

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Windsurf

Config: ~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "cognex": {
      "command": "uvx",
      "args": ["cognex"]
    }
  }
}

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Zed

Config: ~/.config/zed/settings.json

{
  "context_servers": {
    "cognex": {
      "command": {
        "path": "uvx",
        "args": ["cognex"]
      }
    }
  }
}

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Config Format Reference

Tool	Key	Config file
Claude Code	mcpServers	~/.claude.json or .mcp.json
Claude Desktop	mcpServers	claude_desktop_config.json
OpenCode	mcp	opencode.json
Cursor	mcpServers	~/.cursor/mcp.json
VS Code Copilot	servers	.vscode/mcp.json
Cline	mcpServers	cline_mcp_settings.json
Windsurf	mcpServers	mcp_config.json
Zed	context_servers	settings.json

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After Adding Config

Completely close and reopen your AI tool. You should see 20 new Cognex tools available.

Verify in Claude Code:

/mcp
→ cognex: connected

Verify in OpenCode:

/mcp
→ cognex: Connected

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The 20 Tools

Session Management

Tool	Description
substrate_start_session	Start a new work session
substrate_end_session	End session with summary and metrics
substrate_process_transcript	Extract memories from conversation
substrate_report	Get memory health report

Memory

Tool	Description
memory_add	Add a memory (fact, preference, decision, pattern)
memory_search	Search memories with filters
memory_get_context	Get relevant context for current work
memory_decay	Age memories and clean up old ones

Trust Engine

Tool	Description
trust_check	Check if a tool operation needs approval
trust_record	Record approval, denial, or violation
trust_get	Get trust score for a tool
trust_summary	Get trust overview across all tools

Decision Ledger

Tool	Description
ledger_record	Record a decision made
ledger_outcome	Record what happened after the decision
ledger_find_similar	Find similar past decisions

Teleportation

Tool	Description
teleport_create_bundle	Export cognitive state to a signed JSON bundle
teleport_rehydrate	Import cognitive state from a bundle

Swarm

Tool	Description
swarm_compile_intent	Turn natural language into a multi-agent plan

Pattern Intelligence

Tool	Description
pattern_analyze	Discover behavioral patterns from decision history
pattern_stats	Check if enough data exists for pattern analysis

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MCP Prompts

Prompt	Description
cognex://start-session	Initialize session with relevant memories
cognex://end-session	Generate session summary and save insights
cognex://context-for-task	Load context for a specific task
cognex://remember	Save important information to memory
cognex://weekly-summary	Get weekly activity and decision summary

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Example Usage

Remember a Preference

You: "I prefer using type hints everywhere"
AI:  (calls memory_add)
→   Saved to your memory bank

Pick Up Where You Left Off

You: (start new session)
AI:  (calls memory_get_context with "current project")
→   Returns decisions, preferences, and progress from last session
AI:  "Continuing from where we left off — you were building the auth module."

Track a Decision

You: "FastAPI or Flask?"
AI:  "FastAPI has better type safety for your use case."
AI:  (calls ledger_record)

Later...
You: "Did that work out?"
AI:  (calls ledger_outcome — success: true)

Teleport Your Brain to Another Machine

# On machine A
cognex teleport export → generates bundle.json (Ed25519 signed)

# On machine B
cognex teleport import bundle.json → full state restored, signature verified

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Where Data Lives

All data stays local in SQLite under .substrate/ in your project directory:

.substrate/
├── substrate.db   — memories, sessions, cognitive units
├── trust.db       — tool approval history
├── decisions.db   — decision ledger
└── signing_key.pem — Ed25519 private key (generated on first run, never leaves your machine)

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Troubleshooting

"command not found"

pip install cognex
# or use uvx in your config — no install needed

Tools not appearing

1. Completely close and reopen your AI tool (not just reload)
2. Check developer console for JSON parse errors
3. Validate your config JSON at jsonlint.com
4. Run cognex --status to confirm the DB is accessible

Stale uvx cache

uvx cognex@latest  # force fetch latest version

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Development

git clone https://github.com/Gaurav7974/cognex
cd cognex
pip install -e ".[dev]"
pytest tests/ -v

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Roadmap

• v0.1.6 — Cognitive Units: structured decisions with rationale, scope, and confidence
• v0.1.7 — Selective retrieval: load only what matters for the current task
• v0.1.8 — Audited handoff protocol: full CHP compliance for multi-agent workflows
• v0.2.0 — Persistent agent identity: agents that resume instantly with full cognitive context

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License

MIT — free to use, modify, and distribute.

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Need Help?

• Issues: https://github.com/Gaurav7974/cognex/issues
• PyPI: https://pypi.org/project/cognex/
• Docs: see docs/ folder