Skip to content
Conduit

mcp server

christina

Autonomous Cognitive Amplifier for AI Coding Agents — CPG AST Radar, Sandboxed RLM, OKF Semantic Memory & Swarm Concurrency

amadeus-ex-machina/christinacommunitylistedunreviewed

Set up

Runs on your computer. Pick your agent and operating system.

Before you start

  • uv (`curl -LsSf https://astral.sh/uv/install.sh | sh`)
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "christina": {
      "command": "uvx",
      "args": [
        "christina"
      ]
    }
  }
}

same format Cursor, GitHub Copilot CLI, Junie, JetBrains AI Assistant, Augment (Auggie CLI), Factory Droid, Kiro, Devin CLI +12

Values in angle brackets are placeholders. Restart Claude Desktop after editing its config.Claude Desktop docs

README

synced Oct 23, 2026

Project Christina: Autonomous Cognitive Amplifier

Python 3.11+ License: MIT Dependencies Tests FastMCP Compliant Code Style: Ponytail Ultra

Host: Google Antigravity Host: OpenCode Host: Claude Desktop Host: OpenAI Codex CLI

Quick Start • Architecture • MCP Tools • CLI Reference • Documentation • Contributing


🌟 Executive Overview: Eliminating Context Rot

Modern AI coding agents fail on large codebases ($10\text{M}+$ tokens) not due to reasoning limitations, but due to Context Rot: attention distraction, unindexed prompt pollution, lost architectural constraints across context wipes, and uncoordinated swarm collisions.

Project Christina solves this through an integrated, high-performance cognitive trinity:

  1. RLM (Recursive Language Models — Context as a Variable): Moves massive codebases out of conversational prompt transcripts into sandboxed heap variables (context). Agents execute bounded sub-queries ($D \le 2, N \le 20$) and transactional copy-on-write (CoW) Python control loops with automated rollback.
  2. Graphify (Deterministic CPG & AST Radar): Builds an in-memory SQLite3 WAL call graph delivering sub-0.3ms recursive CTE queries, transitive blast radius calculation, and God node centrality ranking with a 71.5x token discovery reduction.
  3. OKF (Durable Semantic Memory & Epistemic Evolution): Sub-microsecond regex frontmatter parsing ($6.72\ \mu\text{s}$/doc), formal AGM belief revision, Ebbinghaus decay, and Mark-and-Sweep epistemic garbage collection with an automated $\le 400$-token post-compaction memory recovery anchor.
  4. Cross-Project Epistemic Distillation: Anonymizes proprietary code into mathematical archetypes with a strict Zero-Information Leakage invariant ($\mathcal{I} = 0$), multi-base Shannon entropy secret scrubbing, and Bayesian invariant aggregation across code repositories.
  5. Swarm Concurrency Control: Decentralized multi-agent execution using Kung-Robinson Optimistic Concurrency Control (OCC), Tree-CRDT 3-way AST merge, and Linda tuple-space blackboard.

🏛️ Tri-Pillar Cognitive Architecture

                                  ┌─────────────────────────────────────────┐
                                  │           SUPERVISOR / AGENT            │
                                  │  (Antigravity / OpenCode / Claude / AI) │
                                  └────────────────────┬────────────────────┘
                                                       │ JSON-RPC 2.0 (stdio)
                                                       ▼
┌───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│                                            PROJECT CHRISTINA FAST-MCP GATEWAY                                     │
├──────────────────────────────────────┬────────────────────────────────────┬───────────────────────────────────────┤
│          PILLAR 1: RLM ENGINE        │       PILLAR 2: GRAPHIFY CPG       │        PILLAR 3: OKF MEMORY           │
│         (Context as Variable)        │          (AST Code Radar)          │         (Semantic Evolution)          │
├──────────────────────────────────────┼────────────────────────────────────┼───────────────────────────────────────┤
│ • Out-of-core Heap Variables         │ • In-Memory SQLite3 WAL Graph      │ • Sub-microsecond OKF Regex Parser    │
│ • Transactional CoW Rollback         │ • Sub-0.3ms Transitive Blast Query │ • Formal AGM Belief Revision          │
│ • 3-Phase EGRI Invariant Linter      │ • Composite God-Node Centrality    │ • Ebbinghaus Forgetting & GC          │
│ • Dynamic Governor (D<=2, N<=20)     │ • Circular Dependency & Wave Sort  │ • Symbol-to-ADR Constraints           │
└──────────────────────────────────────┴────────────────────────────────────┴───────────────────────────────────────┘
                                                       │
                                                       ▼
┌───────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│                                        DECENTRALIZED SWARM & DISTILLERY                                           │
├───────────────────────────────────────────────────────────────────┬───────────────────────────────────────────────┤
│                    SWARM CONCURRENCY BLACKBOARD                   │         GLOBAL EPISTEMIC DISTILLERY           │
├───────────────────────────────────────────────────────────────────┼───────────────────────────────────────────────┤
│ • Kung-Robinson Optimistic Concurrency Control (OCC)              │ • Zero-Information Leakage (I = 0)           │
│ • Semantic Tree-CRDT 3-Way AST Merge Resolution                   │ • Multi-Base Shannon Entropy Secret Redaction │
│ • Linda Tuple Space (`out`, `rd`, `in`, `eval`, `digest`)         │ • Bayesian Invariant Distillation (0700 Fence)│
└───────────────────────────────────────────────────────────────────┴───────────────────────────────────────────────┘

Mermaid Flowchart

flowchart TD
    Host[Host Agent Context] -->|JSON-RPC 2.0 stdio| MCP[Christina FastMCP Server]
    
    subgraph Trinity["Autonomous Cognitive Trinity"]
        MCP -->|cpg_query| CPG[Graphify CPG Radar<br/><i>sub-0.3ms SQLite WAL</i>]
        MCP -->|rlm_execute| RLM[RLM Sandbox<br/><i>Transactional CoW REPL</i>]
        MCP -->|memory_evolve| OKF[OKF Semantic Memory<br/><i>AGM Revision & Epistemic GC</i>]
    end
    
    subgraph SwarmDistill["Swarm & Cross-Project Substrate"]
        MCP -->|swarm_blackboard| OCC[Swarm Concurrency<br/><i>Kung-Robinson OCC + Tree-CRDT</i>]
        OKF -->|distill_global| Distill[Global Epistemic Distillery<br/><i>Anonymized Archetypes (I=0)</i>]
    end

    CPG -.->|Blast Radius & Waves| OCC
    RLM -.->|Isolated Sub-Calls| Host
    OKF -.->|ADR Anchor <=400 Tokens| Host

🚀 1-Command Zero-Friction Installation

Christina installs in seconds without background daemons, native compilation, or root privileges:

cd christina
./install.sh

Automated Diagnostic Preflight

./install.sh doctor
================================================================
 Christina Cognitive Amplifier Diagnostics (v1.0.0)
================================================================
✓ Python Version: 3.11+ (Requirement satisfied)
✓ SQLite3 in-memory WAL Engine: Ready
✓ OKF Semantic Memory Engine: Ready
✓ Google Antigravity Plugin: Registered
✓ OpenCode Plugin: Registered
✓ Global memory directory: ~/.config/christina/global_memory (0700 fenced)
================================================================
✅ All systems functional.

Run Full Test Suite (62/62 Passed in <1.2s)

./install.sh test
# Or with pytest directly:
pytest tests/ -v

🛠️ The Canonical FastMCP Tool Matrix

Christina exposes 4 unified JSON-RPC 2.0 stdio tools compatible with any MCP host:

ToolCategoryKey Capabilities & ModesPerformance Bound
cpg_queryAST Code Radarblast_radius, def_use, cfg, vinterfaces, god_nodes, cycles, waves, info$<0.3\text{ms}$ in-memory traversal
rlm_executeSandboxed ExecutionSub-agent MapReduce, transactional CoW REPL, 3-phase EGRI linting, compute governor$D \le 2, N \le 20$ recursion bound
memory_evolveSemantic Memorysearch, persist, revise (AGM), gc (Ebbinghaus Mark-and-Sweep), distill_global, query_global$6.72\ \mu\text{s}$/doc parsing
swarm_blackboardSwarm Concurrencyout, rd, in, eval, occ_validate (Kung-Robinson OCC), tree_merge (Tree-CRDT), digestLock-free optimistic validation

MCP Tool Invocations

1. Blast Radius Analysis (cpg_query)

{
  "name": "cpg_query",
  "arguments": {
    "symbol": "PaymentGateway",
    "mode": "blast_radius",
    "depth": 3
  }
}

2. Transactional Sub-Query Execution (rlm_execute)

{
  "name": "rlm_execute",
  "arguments": {
    "query": "Audit error recovery handling in database connection pool",
    "scope_paths": ["src/db/", "src/pools/"]
  }
}

3. Semantic Memory Search with Symbol Constraint (memory_evolve)

{
  "name": "memory_evolve",
  "arguments": {
    "action": "search",
    "query": "zero-trust authentication policy",
    "linked_symbols": ["AuthMiddleware"]
  }
}

4. Swarm OCC Conflict Validation (swarm_blackboard)

{
  "name": "swarm_blackboard",
  "arguments": {
    "action": "occ_validate",
    "worker_id": "worker_security_audit",
    "read_version": 4,
    "read_set": ["AuthMiddleware", "SessionToken"],
    "write_set": ["AuthMiddleware"]
  }
}

⚡ CLI Quick Reference

# 1. Scan codebase and index AST knowledge graph into in-memory SQLite3 WAL
python3 -m christina.cli scan .

# 2. Calculate static blast radius for a target symbol
python3 -m christina.cli blast AuthService --depth 3

# 3. List top God Nodes ranked by composite degree centrality
python3 -m christina.cli god-nodes --limit 10

# 4. Search OKF institutional memory, ADRs, and symbol constraints
python3 -m christina.cli memory "connection pool timeout" --symbol DatabasePool

# 5. Run FastMCP JSON-RPC 2.0 stdio server
python3 -m christina.cli serve

# 6. Execute system diagnostics
python3 -m christina.cli doctor

🔌 Multi-Host Compatibility & Setup

Christina includes seamless 1-command registration across all standard AI agent hosts:

1. Google Antigravity CLI (agy)

Automatically symlinked to ~/.gemini/antigravity-cli/plugins/christina and registered in ~/.gemini/antigravity-cli/mcp_config.json.

2. OpenCode

Automatically registered in ~/.config/opencode/plugins/christina and ~/.config/opencode/opencode.json.

3. Claude Desktop

Automatically configured in ~/.claude/claude_desktop_config.json (or Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "christina": {
      "command": "python3",
      "args": ["-m", "christina.bridge.mcp_server"],
      "env": {
        "PYTHONPATH": "/path/to/christina"
      }
    }
  }
}

4. OpenAI Codex CLI

Automatically registered in ~/.config/codex/config.json.


🪮 Ponytail Ultra: Zero-Dependency Guarantee

Project Christina is strictly engineered under Ponytail Ultra discipline:

  • Zero External Runtime Dependencies: Uses Python standard library only (ast, sqlite3, re, json, hashlib, fcntl, math, pathlib, typing).
  • Zero Heavy Daemons: No Docker, no Neo4j, no ChromaDB, no Redis. In-memory SQLite3 WAL and POSIX file locks deliver sub-millisecond execution with $0\text{MB}$ idle background RAM.
  • Strict Code Brevity: Every module is concise ($<250$ LOC), cohesive, and self-contained.

📚 Documentation & Guides

DocumentDescription
Getting Started GuideStep-by-step setup, verification, and first agent workflow.
Skills TaxonomyProgressive disclosure skill definitions (cpg, rlm, memory, swarm).
Contributing GuidePonytail Ultra development guidelines, Nix setup, test suites, and ADR workflow.
Security PolicyZero-information leakage ($\mathcal{I} = 0$), Shannon entropy secret scrubbing, and containment.
ChangelogDetailed release notes and version history.

📜 License

Project Christina is distributed under the open-source MIT License.

Copyright (c) 2026 Christina Engineering Swarm & Contributors.

↑↓ navigate openesc close