Daemon-MCP

Daemon-MCP

Daem0n-MCP provides AI agents with persistent, semantically indexed memory to track decisions, rules, and outcomes across sessions. It actively prevents repetitive mistakes by enforcing context checks and prioritizing information about past failures during recall. Best for Claude Code.

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Daem0nMCP

        ,     ,
       /(     )\
      |  \   /  |      "I am Daem0n, keeper of memories,
       \  \ /  /        guardian of decisions past..."
        \  Y  /
         \ | /
          \|/
           *

AI Memory & Decision System - Give AI agents persistent memory and consistent decision-making with actual semantic understanding.

What's New in v2.16.0

Sacred Covenant Enforcement

The Sacred Covenant is now enforced, not just advisory:

  • requires_communion: Tools block with COMMUNION_REQUIRED until get_briefing() is called
  • requires_counsel: Mutating tools block with COUNSEL_REQUIRED until context_check() is called
  • Preflight tokens: context_check() returns a cryptographic token valid for 5 minutes
  • Remedies: Each block includes the exact tool call needed to fix it

Affected tools:

  • Communion required: remember, remember_batch, add_rule, update_rule, record_outcome, link_memories, pin_memory, archive_memory, prune_memories, cleanup_memories, compact_memories
  • Exempt (read-only): recall, recall_for_file, search_memories, find_code, analyze_impact, check_rules, list_rules

MCP Resources (Dynamic Context Injection)

Resources that Claude Desktop/Code can subscribe to for automatic context:

Resource URI Content
daem0n://warnings/{project_path} All active warnings
daem0n://failed/{project_path} Failed approaches to avoid
daem0n://rules/{project_path} All configured rules
daem0n://context/{project_path} Combined context (warnings + failed + rules)
daem0n://triggered/{file_path} Auto-recalled context for a file

Claude Code 2.1.3 Compatibility

  • Fixed daem0n_pre_edit_hook.py to use MCP HTTP instead of removed check-triggers CLI command
  • Hooks now communicate directly with MCP server for context triggers

What's New in v2.15.0

Iteration 1: Search Quality

  • Configurable hybrid weight: DAEM0NMCP_HYBRID_VECTOR_WEIGHT (0.0-1.0)
  • Result diversity: DAEM0NMCP_SEARCH_DIVERSITY_MAX_PER_FILE limits same-file results
  • Tag inference: Auto-adds bugfix, tech-debt, perf, warning tags

Iteration 2: Code Entity Fidelity

  • Qualified names: Entities have module.Class.method identifiers
  • Stable IDs: Line changes don't invalidate entity IDs
  • Import extraction: Files track their imports for dependency analysis

Iteration 3: Incremental Indexing

  • File hash tracking: Only re-parses changed files
  • index_file_if_changed(): Efficient single-file re-indexing
  • FileHash model: Persists content hashes

Iteration 4: Performance & UX

  • Parse tree caching: Avoids re-parsing unchanged files
  • Extended config: embedding_model, parse_tree_cache_maxsize
  • Enhanced health: Code index stats, staleness detection

What's New in v2.14.0

Active Working Context (MemGPT-style)

Always-hot memory layer that keeps critical information front and center:

  • set_active_context(memory_id) - Pin critical memories to active context
  • get_active_context() - Get all hot memories for current focus
  • remove_from_active_context(memory_id) - Remove from hot context
  • clear_active_context() - Clear all hot memories
  • Auto-included in get_briefing() responses
  • Failed decisions auto-activate with high priority
  • Max 10 items to prevent context bloat

Temporal Versioning

Track how memories evolve over time:

  • Auto-creates versions on memory creation, outcome recording, relationship changes
  • get_memory_versions(memory_id) - Get full version history
  • get_memory_at_time(memory_id, timestamp) - Query historical state
  • Enables questions like "What did we believe about X last month?"

Hierarchical Summarization

GraphRAG-style community detection and layered recall:

  • rebuild_communities() - Detect clusters by tag co-occurrence
  • list_communities() - Get summaries for high-level overview
  • get_community_details(id) - Drill down to member memories
  • recall_hierarchical(topic) - Layered retrieval: summaries then details
  • Auto-generated community names from dominant tags

Auto Entity Extraction (Cognee-style)

Auto-extract and link code entities from memory content:

  • Auto-extracts functions, classes, files, concepts from memories on remember()
  • recall_by_entity(name) - Get all memories mentioning an entity
  • list_entities() - Most frequently mentioned entities
  • backfill_entities() - Extract entities from existing memories
  • Enables queries like "show everything about UserService"

Contextual Recall Triggers (Knowledge Graph MCP-style)

Auto-recall memories without explicit calls based on context patterns:

  • add_context_trigger(pattern, topic) - Define auto-recall rules
  • check_context_triggers(file_path) - Get triggered context
  • list_context_triggers() / remove_context_trigger(id)
  • Supports file patterns, tag matching, entity matching
  • Integrated with pre-edit hooks for automatic injection
  • MCP Resource: daem0n://triggered/{file_path}

What's New in v2.13.0

  • Passive Capture (Auto-Remember): Memories without manual calls
    • Pre-edit hook: Auto-recalls memories for files being modified
    • Post-edit hook: Suggests remember() for significant changes
    • Stop hook: Auto-extracts decisions from Claude's responses
    • CLI remember command for hook integration
    • See hooks/settings.json.example for configuration

What's New in v2.12.0

  • Endless Mode (Context Compression): Reduce token usage by 50-75%
    • recall(topic, condensed=True) - Returns compressed memories
    • Strips rationale, context fields; truncates content to 150 chars
    • Focus areas in briefings use condensed mode automatically
    • Inspired by memvid-mind's token efficiency approach

What's New in v2.11.0

  • Linked Projects (Multi-Repo Support): Work across related repositories
    • Link client/server or other related repos for cross-awareness
    • link_projects() / unlink_projects() / list_linked_projects()
    • recall(include_linked=True) - Search across linked repos
    • consolidate_linked_databases() - Merge child DBs into unified parent
    • get_briefing() now shows linked project warnings/stats
    • See docs/multi-repo-setup.md for full guide
    • New skill: summon_daem0n for project setup guidance

Previous Features (v2.10.0)

  • Code Understanding Layer (Phase 2): The Daem0n now understands your code structure
    • Multi-language AST parsing via tree-sitter-language-pack
    • Supports: Python, TypeScript, JavaScript, Go, Rust, Java, C, C++, C#, Ruby, PHP
    • Extracts: classes, functions, methods, signatures, docstrings
    • New MCP tools:
      • index_project - Index code entities for understanding
      • find_code - Semantic search across code entities
      • analyze_impact - Analyze what changing an entity would affect
    • CLI: python -m daem0nmcp.cli index
    • New models: CodeEntity, MemoryCodeRef

Previous Features (v2.9.0)

  • Qdrant Vector Backend (Phase 0): Persistent vector storage replaces SQLite blob storage

    • Qdrant local mode (file-based, no server required)
    • Hybrid search: TF-IDF + vector similarity (0.3 weight)
    • Migration script: python -m daem0nmcp.migrations.migrate_vectors
  • Proactive File Watcher (Phase 1): The Daem0n now watches your files proactively

    • Monitors file changes and notifies when files with associated memories are modified
    • Multi-channel notifications:
      • System notifications: Desktop alerts via plyer
      • Log file: JSON-lines at .daem0nmcp/storage/watcher.log
      • Editor poll: JSON at .daem0nmcp/storage/editor-poll.json for IDE plugins
    • Start with: python -m daem0nmcp.cli watch
    • Configurable debouncing, skip patterns, extension filters

Previous Features (v2.8.0)

  • Automatic Tool Reminders (Stop Hook): Claude Code hooks that detect task completion and remind to record outcomes
  • Enhanced SessionStart Hook: Now reminds to commune with get_briefing() at session start
  • Hook Scripts: New hooks/ directory with reusable Python scripts for Claude Code integration

Previous Features (v2.7.0)

  • Pre-Commit Enforcement: Git hooks that actually block commits when memory discipline is broken
    • Blocks commits with decisions >24h old that lack recorded outcomes
    • Blocks commits modifying files with known failed approaches
    • Warns on recent pending decisions and file warnings
  • CLI Resolution Tools: New commands to resolve blocking issues
    • status - Show pending decisions and what's blocking
    • record-outcome - Record outcomes directly from CLI
    • install-hooks / uninstall-hooks - Manage git hooks
  • Automatic Session Tracking: remember() now auto-tracks decisions as pending

Previous Features (v2.6.0)

  • Enhanced Bootstrap: First-run context collection extracts 7 memory categories automatically
  • Smarter Session Start: get_briefing() reports exactly what was ingested

Previous Features (v2.5.0)

  • Windows HTTP Transport: Full Windows support via streamable-http (bypasses stdio bugs)
  • Ritual-Themed Installation: Summon_Daem0n.md and Banish_Daem0n.md for fun
  • Claude Code Hooks: Auto-reminders to use memory tools
  • Protocol Skill: daem0nmcp-protocol skill for Superpowers users

Core Features (v2.1+)

  • TF-IDF Semantic Search: Real similarity matching, not just keyword overlap
  • Memory Decay: Recent memories weighted higher than old ones
  • Conflict Detection: Warns when new decisions contradict past failures
  • Failed Decision Boosting: Past mistakes surface prominently in recalls
  • File-Level Memories: Associate memories with specific files
  • Vector Embeddings: sentence-transformers for enhanced semantic matching

Why Daem0nMCP?

AI agents start each session fresh. They don't remember:

  • What decisions were made and why
  • Patterns that should be followed
  • Warnings from past mistakes

Markdown files don't solve this - the AI has to know to read them and might ignore them.

Daem0nMCP provides ACTIVE memory - it surfaces relevant context when the AI asks about a topic, enforces rules before actions, and learns from outcomes.

What Makes This Different

Unlike keyword-based systems:

  • Semantic matching: "creating REST endpoint" matches rules about "adding API route"
  • Time decay: A decision from yesterday matters more than one from 6 months ago
  • Conflict warnings: "You tried this approach before and it failed"
  • Learning loops: Record outcomes, and failures get boosted in future recalls

Quick Start

The Easy Way (Recommended)

  1. Copy Summon_Daem0n.md to your project
  2. Start a Claude Code session in that project
  3. Claude will read the file and perform the summoning ritual automatically

Manual Installation

# Clone the repository
git clone https://github.com/DasBluEyedDevil/Daem0n-MCP.git ~/Daem0nMCP

# Install
pip install -e ~/Daem0nMCP

# Run the MCP server (Linux/macOS)
python -m daem0nmcp.server

# Run the MCP server (Windows - use HTTP transport)
python ~/Daem0nMCP/start_server.py --port 9876

Installation by Platform

Linux / macOS (stdio transport)

# Find your Python path
python3 -c "import sys; print(sys.executable)"

# Register with Claude Code (replace <PYTHON_PATH>)
claude mcp add daem0nmcp --scope user -- <PYTHON_PATH> -m daem0nmcp.server

# Restart Claude Code

Windows (HTTP transport required)

Windows has a known bug where Python MCP servers using stdio transport hang indefinitely. Use HTTP transport instead:

  1. Start the server (keep this terminal open):
python ~/Daem0nMCP/start_server.py --port 9876

Or use start_daem0nmcp_server.bat

  1. Add to ~/.claude.json:
{
  "mcpServers": {
    "daem0nmcp": {
      "type": "http",
      "url": "http://localhost:9876/mcp"
    }
  }
}
  1. Start Claude Code (after server is running)

Core Tools (42 Total)

Memory Tools

Tool Purpose
remember Store a memory with conflict detection
remember_batch Store multiple memories efficiently in one transaction
recall Semantic memory retrieval by topic (supports condensed=True for token savings)
recall_for_file Get memories linked to a specific file
search_memories Search across all memories
find_related Discover connected memories
record_outcome Track if a decision worked or failed
pin_memory Pin memories to prevent pruning and boost relevance
archive_memory Hide memories from recall while preserving history
compact_memories Consolidate old episodic memories into summaries
get_memory_versions Get full version history for a memory
get_memory_at_time Query historical state of a memory at a specific time

Rule Tools

Tool Purpose
add_rule Create decision tree nodes
check_rules Semantic rule matching
update_rule Modify existing rules
list_rules Show all configured rules

Session & Context Tools

Tool Purpose
get_briefing Smart session start with git awareness
context_check Combined recall + rules in one call
set_active_context Pin memory to active working context
get_active_context Get all hot memories for current focus
remove_from_active_context Remove memory from active context
clear_active_context Clear all hot memories

Graph Memory Tools

Tool Purpose
link_memories Create causal relationships between memories
unlink_memories Remove relationships between memories
trace_chain Traverse memory graph (forward/backward)
get_graph Visualize memory relationships (JSON or Mermaid)

Hierarchical Summarization Tools

Tool Purpose
rebuild_communities Detect memory clusters by tag co-occurrence
list_communities Get community summaries for high-level overview
get_community_details Drill down to member memories in a community
recall_hierarchical Layered retrieval: community summaries then details

Code Understanding Tools

Tool Purpose
index_project Index code entities (classes, functions, methods)
find_code Semantic search across code entities
analyze_impact Analyze what changing an entity would affect

Utility Tools

Tool Purpose
scan_todos Find TODO/FIXME/HACK comments
propose_refactor Get refactoring context for a file
ingest_doc Import external documentation

Maintenance Tools

Tool Purpose
rebuild_index Force rebuild TF-IDF and vector indexes
export_data Export all memories and rules as JSON
import_data Import memories and rules from JSON
prune_memories Remove old, low-value memories (with protection)
cleanup_memories Find and merge duplicate memories
health Get server health, version, and statistics

Usage Examples

Store a Memory

remember(
    category="decision",  # decision, pattern, warning, or learning
    content="Use JWT tokens instead of sessions",
    rationale="Need stateless auth for horizontal scaling",
    tags=["auth", "architecture"],
    file_path="src/auth/jwt.py"  # optional file association
)

Retrieve Memories

recall("authentication")
# Returns: decisions, patterns, warnings, learnings about auth
# Sorted by: semantic relevance × recency × importance

recall_for_file("src/auth/jwt.py")
# Returns: all memories linked to this file

Create Rules

add_rule(
    trigger="adding new API endpoint",
    must_do=["Add rate limiting", "Write integration test"],
    must_not=["Use synchronous database calls"],
    ask_first=["Is this a breaking change?"]
)

Track Outcomes

record_outcome(memory_id=42, outcome="JWT auth works great", worked=True)
record_outcome(memory_id=43, outcome="Caching caused stale data", worked=False)
# Failed decisions get 1.5x boost in future recalls

Session Start

get_briefing(focus_areas=["authentication", "API"])
# First run: Creates 6-7 memories from project structure, README, manifests, etc.
# Returns: stats, recent decisions, warnings, failed approaches,
# git changes, bootstrap summary, plus pre-fetched context for focus areas

Endless Mode (Token Compression)

# Full recall (default) - ~40KB response
recall("authentication")

# Condensed recall - ~10KB response (75% smaller)
recall("authentication", condensed=True)
# Returns: truncated content, no rationale/context, minimal fields

# Briefings automatically use condensed mode for focus areas
get_briefing(focus_areas=["auth", "database", "api"])
# Focus area results are pre-compressed

Import External Docs

ingest_doc("https://stripe.com/docs/api/charges", "stripe")
# Later: recall("stripe") to retrieve

AI Agent Protocol

The recommended workflow for AI agents:

SESSION START
    └─> get_briefing()

BEFORE CHANGES
    └─> context_check("what you're doing")
    └─> recall_for_file("path/to/file.py")

AFTER DECISIONS
    └─> remember(category, content, rationale, file_path)

AFTER IMPLEMENTATION
    └─> record_outcome(memory_id, outcome, worked)

See Summon_Daem0n.md for the complete protocol (with ritual theme for fun).

Claude Code Integration

Hooks (Auto-Reminders)

Add to .claude/settings.json:

{
  "hooks": {
    "PreToolUse": [{
      "matcher": "Edit|Write",
      "hooks": [{
        "type": "command",
        "command": "echo '[Daem0n] Check memories before modifying'"
      }]
    }],
    "PostToolUse": [{
      "matcher": "Edit|Write",
      "hooks": [{
        "type": "command",
        "command": "echo '[Daem0n] Consider calling remember()'"
      }]
    }]
  }
}

Passive Capture Hooks

For fully automatic memory capture, enable all hooks in .claude/settings.json:

{
  "hooks": {
    "PreToolUse": [{
      "matcher": "Edit|Write|NotebookEdit",
      "hooks": [{
        "type": "command",
        "command": "python3 \"$HOME/Daem0nMCP/hooks/daem0n_pre_edit_hook.py\""
      }]
    }],
    "PostToolUse": [{
      "matcher": "Edit|Write",
      "hooks": [{
        "type": "command",
        "command": "python3 \"$HOME/Daem0nMCP/hooks/daem0n_post_edit_hook.py\""
      }]
    }],
    "Stop": [{
      "matcher": "",
      "hooks": [{
        "type": "command",
        "command": "python3 \"$HOME/Daem0nMCP/hooks/daem0n_stop_hook.py\""
      }]
    }]
  }
}

What each hook does:

  • Pre-edit: Shows warnings, patterns, and past decisions for files before you modify them
  • Post-edit: Suggests calling remember() when you make significant changes
  • Stop: Auto-extracts decisions from Claude's responses and creates memories

Protocol Skill

For Superpowers users, a skill is included at .claude/skills/daem0nmcp-protocol/SKILL.md that enforces the memory protocol.

How It Works

TF-IDF Similarity

Instead of simple keyword matching, Daem0nMCP builds TF-IDF vectors for all stored memories and queries. This means:

  • "authentication" matches memories about "auth", "login", "OAuth"
  • Rare terms (like project-specific names) get higher weight
  • Common words are automatically de-emphasized

Memory Decay

weight = e^(-λt) where λ = ln(2)/half_life_days

Default half-life is 30 days. A 60-day-old memory has ~25% weight. Patterns and warnings are permanent (no decay).

Conflict Detection

When storing a new memory, it's compared against recent memories:

  • If similar content failed before → warning about the failure
  • If it matches an existing warning → warning surfaced
  • If highly similar content exists → potential duplicate flagged

Failed Decision Boosting

Memories with worked=False get a 1.5x relevance boost in recalls. Warnings get a 1.2x boost. This ensures past mistakes surface prominently.

Data Storage

Each project gets isolated storage at:

<project_root>/.daem0nmcp/storage/daem0nmcp.db

Legacy Migration

If upgrading from DevilMCP, data is automatically migrated from .devilmcp/ to .daem0nmcp/.

Configuration

Environment variables (prefix: DAEM0NMCP_):

Variable Default Description
DAEM0NMCP_PROJECT_ROOT . Project root path
DAEM0NMCP_STORAGE_PATH auto Override storage location
DAEM0NMCP_LOG_LEVEL INFO Logging level

Architecture

daem0nmcp/
├── server.py       # MCP server with 42+ tools (FastMCP)
├── memory.py       # Memory storage & semantic retrieval
├── rules.py        # Rule engine with TF-IDF matching
├── similarity.py   # TF-IDF index, decay, conflict detection
├── vectors.py      # Vector embeddings (sentence-transformers)
├── covenant.py     # Sacred Covenant enforcement decorators & preflight tokens
├── code_indexer.py # Code understanding via tree-sitter (Phase 2)
├── watcher.py      # Proactive file watcher daemon (Phase 1)
├── database.py     # SQLite async database
├── models.py       # 10+ tables: memories, rules, memory_relationships,
│                   #             session_state, code_entities, memory_code_refs,
│                   #             communities, context_triggers, memory_versions, etc.
├── enforcement.py  # Pre-commit enforcement & session tracking
├── hooks.py        # Git hook templates & installation
├── cli.py          # Command-line interface
├── migrations/     # Database schema migrations
└── config.py       # Pydantic settings

.claude/
└── skills/
    └── daem0nmcp-protocol/
        └── SKILL.md   # Protocol enforcement skill

Summon_Daem0n.md   # Installation instructions (ritual theme)
Banish_Daem0n.md   # Uninstallation instructions
start_server.py    # HTTP server launcher (Windows)

CLI Commands

# Check a file against memories and rules
python -m daem0nmcp.cli check <filepath>

# Get session briefing/statistics
python -m daem0nmcp.cli briefing

# Scan for TODO/FIXME/HACK comments
python -m daem0nmcp.cli scan-todos [--auto-remember] [--path PATH]

# Index code entities (Phase 2)
python -m daem0nmcp.cli index [--path PATH] [--patterns **/*.py **/*.ts ...]

# Run database migrations (usually automatic)
python -m daem0nmcp.cli migrate [--backfill-vectors]

Enforcement Commands

# Check staged files (used by pre-commit hook)
python -m daem0nmcp.cli pre-commit [--interactive]

# Show pending decisions and blocking issues
python -m daem0nmcp.cli status

# Record outcome for a decision
python -m daem0nmcp.cli record-outcome <id> "<outcome>" --worked|--failed

# Install git hooks
python -m daem0nmcp.cli install-hooks [--force]

# Remove git hooks
python -m daem0nmcp.cli uninstall-hooks

All commands support --json for machine-readable output and --project-path to specify the project root.

Upgrading

Upgrading Daem0n-MCP is straightforward:

1. Update the Code

# If installed from source (recommended)
cd ~/Daem0nMCP && git pull && pip install -e .

# If installed via pip
pip install --upgrade daem0nmcp

Important: The pip install -e . step is required to install all dependencies:

  • qdrant-client - Vector database for semantic search
  • watchdog - File watching for proactive notifications
  • plyer - Desktop notifications
  • tree-sitter-language-pack - Multi-language code parsing (Python 3.14 compatible)

All dependencies are required for full functionality.

2. Restart Claude Code

After updating, restart Claude Code to load the new MCP tools.

3. Migrations Run Automatically

Database migrations are applied automatically when any MCP tool runs. The first time you use get_briefing(), remember(), or any other tool after upgrading, the database schema is updated.

No manual migration step required.

4. Install Enforcement Hooks

Pre-commit hooks block commits when decisions lack outcomes:

python -m daem0nmcp.cli install-hooks

5. Index Your Codebase

Enable code understanding by indexing your project:

python -m daem0nmcp.cli index

This parses your code with tree-sitter (supports Python, TypeScript, JavaScript, Go, Rust, Java, C, C++, C#, Ruby, PHP) and enables semantic code search via find_code() and impact analysis via analyze_impact().

Troubleshooting

MCP Tools Not Available in Claude Session

Symptom: claude mcp list shows daem0nmcp connected, but Claude can't use mcp__daem0nmcp__* tools.

Cause: Known Claude Code bug (#2682) where MCP tools are discovered but not injected into Claude's toolbox.

Fixes:

  1. Start server before Claude Code:

    # Terminal 1: Start Daem0n server first
    python ~/Daem0nMCP/start_server.py --port 9876
    
    # Wait for "Uvicorn running on http://localhost:9876"
    
    # Terminal 2: Then start Claude Code
    claude
    
  2. Re-register the server:

    claude mcp remove daem0nmcp -s user
    claude mcp add daem0nmcp http://localhost:9876/mcp -s user
    
  3. Verify tools are available:

    • Claude should show mcp__daem0nmcp__* tools in its toolbox
    • If Claude tries claude mcp call bash commands instead, the tools aren't injected

Hooks Not Firing

Symptom: Pre-edit hooks don't show Daem0n context.

Check:

  1. MCP server running: curl http://localhost:9876/mcp should respond
  2. Hooks configured in .claude/settings.json
  3. Project has .daem0nmcp/ directory

Development

# Install in development mode
pip install -e .

# Run tests (432 tests)
pytest tests/ -v --asyncio-mode=auto

# Run server directly
python -m daem0nmcp.server

# Run HTTP server (Windows)
python start_server.py --port 9876

Support

If Daem0nMCP has been useful to you, consider supporting its development:

Ko-fi

Uninstallation

See Banish_Daem0n.md for complete removal instructions, or quick version:

# Remove MCP registration
claude mcp remove daem0nmcp --scope user

# Uninstall package
pip uninstall daem0nmcp

# Remove repository
rm -rf ~/Daem0nMCP

# Remove project data (optional)
rm -rf .daem0nmcp/

    "The system learns from YOUR outcomes.
     Record them faithfully..."
                              ~ Daem0n

Daem0nMCP v2.16.0: Sacred Covenant Enforcement—rigid enforcement decorators, preflight tokens, MCP Resources for dynamic context injection, Claude Code 2.1.3 compatibility.

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