XMEComing Soon

Xanther Memory Engine

Persistent memory for coding agents. XME gives your agent long-term recall — decisions, preferences, and context that persist across sessions, IDEs, and team members. Linked to your codebase architecture via XCE.

The problem with stateless agents

Every new chat, every new task — your agent starts from zero. It doesn't remember what it tried before, what decisions were made, or what your preferences are. You end up re-explaining the same context over and over. Memory Engine fixes that.

How XME + XCE Work Together

🏗️

XCE — Context Engine

Understands your codebase architecture. Knows what code does and how it connects.

🧠

XME — Memory Engine

Remembers decisions, preferences, and history. Linked to architecture nodes in XCE.

Together

Agent knows the code AND remembers what happened. Context + memory = true intelligence.

Agent asks about auth module
  → XCE returns architecture context (files, dependencies, patterns)
  → XME returns memory ("last week we decided to migrate from JWT to sessions")
  → Agent has full picture: code structure + historical decisions

Capabilities

Persistent Memory

Your agent remembers past interactions, decisions, and context — even across restarts and IDE switches.

  • Long-term memory store
  • Contextual recall
  • Automatic memory extraction

Cross-Session State

State carries over between sessions. Your agent picks up right where it left off — no re-explaining.

  • Session continuity
  • State snapshots
  • Cross-IDE persistence

Decision History

Track every decision your agent made and why — full audit trail for debugging and knowledge transfer.

  • Decision logging
  • Reasoning traces
  • Queryable history

User Preferences

Learn coding style, naming conventions, and architectural preferences over time. Applied automatically.

  • Style learning
  • Convention enforcement
  • Team-wide standards

MCP Tools

xme_remember

Store a memory node — decisions, preferences, findings, or any context worth preserving.

xme_recall

Query memories by topic, time range, or relevance to the current task.

xme_session_state

Get/set session state — task progress, open questions, next steps.

xme_preferences

Read/write user and team preferences — coding style, conventions, patterns.

xme_history

Query decision history — what was tried, what worked, what was rejected and why.

Use Cases

Multi-day refactors

Agent remembers what it already explored, what approaches failed, and what's left to do — across days and sessions.

Team knowledge sharing

Shared memory means new team members' agents inherit knowledge about the codebase, conventions, and past decisions.

Debugging continuity

Pick up a debugging session days later — the agent recalls the full investigation trail, hypotheses tested, and findings.

Style consistency

Agent learns your team's coding patterns and applies them automatically across PRs — no more style review comments.

Cross-IDE workflow

Start in Cursor, continue in Claude Code, review in Kiro — memory travels with you across every MCP-compatible tool.

Architecture decisions

Record why architectural choices were made. Future agents (and developers) can query the reasoning behind any decision.

Architecture

┌─────────────────┐     MCP/SSE    ┌─────────────────┐
│  Coding Agent   │◄──────────────►│   XME Server    │
│  (any IDE)      │                │                 │
└─────────────────┘                │  Memory Store   │
         │                         │  + Graph Links  │
         │                         │  + TimeSeries   │
         ▼                         └────────┬────────┘
┌─────────────────┐                         │
│   XCE Server    │◄────────────────────────┘
│  (architecture) │   Offline sync: memories
└─────────────────┘   linked to graph nodes

Memory Types:
  • Decisions    — "We chose X because Y"
  • Preferences  — "Team uses camelCase, 2-space indent"
  • Findings     — "Bug was in auth/middleware.py line 42"
  • State        — "Task 3/5 complete, blocked on API review"
  • History      — "Tried approach A (failed), B (worked)"

Ready to supercharge your coding agents?

Give your agents the context they need to solve real-world issues.