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This project tracks workflow state, tasks, design decisions, and blockers using state-memory-mcp with project slug "state-memory-mcp".
Persistent, branch-aware workflow state memory MCP server for AI coding assistants. Tracks tasks, accepted decisions, and active blockers to prevent session context bloat and speed up development.
This repository also configures its own agents. See what state-memory-mcp tells them →
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This project tracks workflow state, tasks, design decisions, and blockers using state-memory-mcp with project slug "state-memory-mcp".
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This project utilizes vision-memory-mcp to cache visual states, record layout transitions, provide element grounding, and avoid repetitive LLM vision calls.
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This project uses agent-reasoning-mcp with project slug "state-memory-mcp" to manage goals, decompose complex tasks, evaluate situational trade-offs, and track decision rationale.
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This project uses behavior-mcp with project slug "state-memory-mcp" to execute deterministic behavior trees at 60Hz in browser runtimes with reactive triggers and safety guardrails.
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This project uses world-model-mcp with project slug "state-memory-mcp" to maintain a persistent 3D/2D spatial internal world model, entity tracking, object permanence, and movement simulation.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: