anime-mori

Persistent codebase intelligence. Learns patterns, conventions, and architecture from your codebase via tree-sitter AST parsing (12 languages) and remembers across sessions. MCP server with 13 tools for semantic search, pattern prediction, file routing, and project blueprints.

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Anime Mori: Persistent Codebase Intelligence

"Your AI pair programmer finally has a notepad that doesn't get wiped clean."

Overview

Anime Mori is the codebase memory skill of the Cognitive Construct. It solves session amnesia — the problem where AI assistants forget your architecture, naming conventions, and design decisions every time you start a new session.

Built on Rust (tree-sitter AST parsing) + TypeScript (MCP server + orchestration), it learns once and remembers forever via SurrealDB persistence.

Architecture

AI Tool (Claude/Copilot)
  │ MCP Protocol (stdio)
  ▼
TypeScript Server — 13 tools, 4 categories
  │ NAPI bindings
  ▼
Rust Core — tree-sitter, pattern learning, semantic engine
  │
  ▼
Storage — SurrealDB (persistent vectors) + SQLite (structured data)

Commands

`learn <path>`

Analyze and learn from a codebase. Extracts patterns, architecture, and conventions.

npx anime-mori learn ./my-project

`server`

Start the MCP server for AI tool integration.

npx anime-mori server

`search <query>`

Multi-mode codebase search (semantic, text, or pattern-based).

npx anime-mori search "authentication middleware"

`analyze <path>`

Analyze files/directories with concepts, patterns, and complexity metrics.

`insights <query>`

Query learned semantic concepts and relationships.

`patterns`

Get pattern recommendations with examples from your codebase.

`predict`

Predict implementation approach based on your coding history.

`status`

System health check.

MCP Tools (13)

Category	Tools	Description
Core Analysis (2)	`analyze_codebase`, `search_codebase`	File/directory analysis, multi-mode search
Intelligence (7)	`learn_codebase_intelligence`, `get_project_blueprint`, `get_semantic_insights`, `get_pattern_recommendations`, `predict_coding_approach`, `get_developer_profile`, `contribute_insights`	Deep learning, blueprints, predictions
Automation (1)	`auto_learn_if_needed`	Smart auto-learning with staleness detection
Monitoring (3)	`get_system_status`, `get_intelligence_metrics`, `get_performance_status`	Health, analytics, diagnostics

Language Support

Native AST parsing via tree-sitter (12 languages):

TypeScript, JavaScript (JSX/TSX), Python, Rust, Go, Java, C, C++, C#, Svelte, SQL, PHP

Synergies

→ Encyclopedia: Vendored at encyclopedia/scripts/anime-mori/ — encyclopedia can invoke Anime Mori's MCP tools for codebase context during knowledge retrieval
→ Inland Empire: Learned patterns and conventions feed into the subconscious memory layer

Files

src/ — TypeScript source (CLI, MCP server, engines, storage)
rust-core/ — Rust NAPI bindings (tree-sitter parsers, analyzers)
src/mcp-server/server.ts — MCP server entry point
src/cli/cli.ts — CLI entry point
src/engines/ — Semantic and pattern analysis engines
src/storage/ — SurrealDB persistence layer
README.md — Full documentation with setup guides

Repository: Raudbjorn/cognitive-construct
Path: encyclopedia/scripts/anime-mori/SKILL.md
Commit: 319f646

Last updated: 6 days ago
First committed: 6 months ago

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