Skip to main content

Epistemic Graph Memory (v3.0.0)

Epistemic Graph Memory 2D UI Global View

A universal, long-term project memory and structural context tool for AI coding agents (Antigravity, Hermes, Claude, Cursor, Codex, OpenHands, Ollama).

Epistemic Graph Memory provides a local, SQLite-backed knowledge graph with Dynamic Epistemic Trust Decay, First-Class Decision Audit Ledgers, Codebase AST Call-Graph Awareness, Hermes-Class Prompt Snapshots, and Continuous Micro-Compaction.

Exposed natively via the Model Context Protocol (MCP) and CLI.


🌟 Core Features (v3.0.0)

1. 🌲 Hermes-Class Declarative Memory & Auto-Recall Snapshots

  • Prompt-Cache Friendly Snapshots (graph-memory snapshot): Automatically generates ultra-dense, 500-token Markdown snapshots of active, high-trust graph facts (effective_trust >= 0.7) and recent milestones to inject into LLM system prompts on session startup.
  • Continuous Micro-Compaction (distill_session): Based on Hermes Agent micro-compaction principles, verbatim user intent is preserved, while large assistant tool outputs and file reads are continuously distilled into structured graph facts.
  • Episodic Session Logging & FTS5 Search (search-sessions): Logs all multi-session conversation history into SQLite FTS5 for zero-friction historic turn retrieval.

2. ⏳ Dynamic Epistemic Trust Decay

  • Cognitive Forgetting Math: Calculates dynamic, query-time trust decay without mutating baseline data: $$\text{Effective Trust} = \text{Base Trust Score} \times \left(0.5^{\frac{\Delta t}{30.0}}\right)$$
  • Automatic Re-Verification: Re-verifying a node or re-parsing code updates last_verified_at = now(), immediately restoring effective trust to 100%.
  • Decay Retrieval Filtering: search_nodes and serialize_subgraph automatically filter out stale entities below min_trust.

3. 📜 First-Class Multi-Agent Decision Ledger

  • Append-Only Audit Trail (Decision_Ledger): Tracks which agent made what decision, why (rationale), and when.
  • CLI & MCP Querying: Query decision history by agent, node ID, or timeframe (graph-memory query-history --agent Hermes).

4. 🔍 Codebase AST & Call Graph Awareness

  • Polyglot AST Ingestion (ingest-code): Deterministic parsing of Python, TypeScript (.ts, .tsx), JavaScript (.js, .jsx), Go, and Rust repositories via Tree-sitter.
  • Production Call Graphs & Inheritance: Extracts function call chains (Func_A -[CALLS]-> Func_B) and class inheritance (Class_Sub -[EXTENDS]-> Class_Base).
  • Code Snippets & Line Bounds: Extracts exact function signatures, docstrings, line bounds (L10-L45), and code snippets (read_code_snippet).
  • <5ms Single-File Re-parsing (ingest-file): Incremental single-file re-parsing for instant updates during editing.
  • Ghost Component Pruning: Automatically prunes obsolete function/class nodes when source files are updated.

5. 🔀 Entity Merging & Canonical Pointers

  • Soft-Delete Merging (merge_nodes / merge): Merges duplicate entities with canonical pointer resolution (resolve_canonical_id), alias array tracking, and full history propagation.

6. 🎨 2D & GPU-Accelerated 3D Visualizations

  • Interactive HTML Export (export_html): Visualizes graph nodes, relationships, and trust scores in interactive 2D.
  • 3D WebGL Viewer (export-3d): GPU-accelerated 3D force-directed graph visualizer (vis-network@9.1.9).

📦 Installation

pip install epistemic-graph-memory[all]

Note: The [all] extra installs polyglot Tree-sitter AST parser bindings.


🔌 MCP Server Configuration

To use Epistemic Graph Memory natively inside Claude Desktop, Cursor, Antigravity, Hermes, or Codex, add the following to your MCP configuration:

{
  "mcpServers": {
    "graph-memory": {
      "command": "graph-memory-mcp"
    }
  }
}

🚀 Quickstart

1. Ingest Codebase AST & Build Graph

# Parse full codebase AST, call graphs, and inheritance
graph-memory ingest-code .

# Incrementally re-parse a single modified file (<5ms)
graph-memory ingest-file graph_memory/core/engine.py --agent Antigravity --rationale "Refactored trust decay"

2. Generate Active Prompt Snapshot (Hermes Auto-Recall)

# Output prompt-cache friendly Markdown snapshot for system prompt injection
graph-memory snapshot --max-tokens 600 --min-trust 0.7

3. Query Decision History & Search

# Query agent decision audit ledger
graph-memory query-history --agent Hermes --limit 10

# FTS5 search across graph nodes
graph-memory search "effective trust"

# FTS5 search across episodic session logs
graph-memory search-sessions "tree-sitter fallback"

4. Graph Maintenance & 3D Visualization

# Lint for orphan nodes and dangling edges
graph-memory lint --fix

# Perform SQLite database vacuum
graph-memory consolidate

# Export WebGL 3D GPU-Accelerated Graph Viewer
graph-memory export-3d memory_3d.html

🛠️ MCP Tool Reference

MCP Tool Description
get_active_snapshot Returns prompt-cache friendly Markdown snapshot of active high-trust graph facts.
distill_session Performs continuous micro-compaction and fact distillation on session turns.
search_session_history Searches historical conversation transcripts using SQLite FTS5.
query_decision_history Queries global Decision_Ledger by agent, node ID, or timeframe.
read_code_snippet Retrieves exact AST signature, docstring, line bounds, and source code snippet.
ingest_file Incrementally re-parses a single changed file into the AST graph (<5ms).
merge_entities Merges source entity into target entity with canonical pointer redirect.
create_entities Creates multiple entities with trust scores and observation payloads.
create_relations Creates directional relations between entities with trust metrics.
search_nodes FTS5 search across entity names, types, and observation content.
open_nodes Serializes subgraphs around specific central nodes.
read_graph Serializes complete knowledge graph.

💡 Architecture Protocols

Entity Ontologies

  • Fact_Node: Ground-truth facts derived deterministically from AST, Git, or session distillation.
  • Knowledge_Node: High-level architecture, module summaries, and design decisions.
  • Episode_Node: Workflows, completed task sequences, and milestone records (linked with FOLLOWED_BY edges).
  • Release_Node: Formally published software versions and package release records.

📜 Lineage & Acknowledgments

Graph-Memory was inspired by the Open Knowledge Format (OKF) and the Hermes Agent memory architecture.

  • SQLite WAL & FTS5: Powered by local SQLite WAL mode for concurrent multi-agent safety and FTS5 for high-speed indexing.
  • Tree-Sitter: Powered by Tree-sitter for polyglot AST parsing.

📄 License

MIT License. Created by Divyansh Ailani.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

epistemic_graph_memory-3.1.0.tar.gz (30.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

epistemic_graph_memory-3.1.0-py3-none-any.whl (32.7 kB view details)

Uploaded Python 3

File details

Details for the file epistemic_graph_memory-3.1.0.tar.gz.

File metadata

  • Download URL: epistemic_graph_memory-3.1.0.tar.gz
  • Upload date:
  • Size: 30.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.2

File hashes

Hashes for epistemic_graph_memory-3.1.0.tar.gz
Algorithm Hash digest
SHA256 be7585a895b92765053212ed9314774a980b029f7869926ab4053a9f09d4a071
MD5 67b413d19c0cca2a85d6e30ce12e694e
BLAKE2b-256 245ce970596d7c6d0fb87ecefe4b31791bf29890fb98fefd628a1cc2f3fb7408

See more details on using hashes here.

File details

Details for the file epistemic_graph_memory-3.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for epistemic_graph_memory-3.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c2b8123575e2da8cbb5f0385e5b50332ef356e3b36b1e6ee6b06e5d4761bd565
MD5 a66e66c5a326323b3e8d6625d843c3aa
BLAKE2b-256 0ee9053211c56a11646669871e1a1cc9822192d4cc629905038df4ddabc1688d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page