Sequential Thinking Mcp V2

sequential-thinking-mcp-v2 is a local MCP server for structured reasoning, session persistence, and project memory. The current codebase is the older markdown-only implementation; the repository now also contains an approved design and implementation plan for a layered memory architecture better suited to long-running coding-agent work.

Architecture Direction

The approved direction is:

• Markdown as canonical human truth
• qmd for canonical document retrieval
• Zvec for promoted memory artifacts and other non-doc semantic artifacts
• a structured metadata store for lifecycle state
• MCP as the stable tool interface
• cloud-assisted operation first, with local-first fallback when network access fails

Design and plan documents:

• docs/plans/2026-03-08-agent-memory-reasoning-architecture-design.md
• docs/plans/2026-03-08-agent-memory-architecture.md

Why This Changes

The current implementation stores sessions and memories as markdown snapshots. That is simple and inspectable, but it is weak for:

• semantic recall across long-running work
• distinguishing scratch reasoning from durable conclusions
• checkpointing and compaction
• large-codebase context management
• reliable handoff between agents or sessions

The target architecture keeps the human-readable markdown layer and adds explicit retrieval, promotion, and metadata boundaries.

Memory Model

Canonical Truth

Markdown remains the official human-maintained truth:

• design docs
• ADRs
• runbooks
• module maps
• handoff docs

Semantic Recall

Zvec is intended to index more than just "memories". It should cover promoted non-doc artifacts such as:

• promoted memories
• investigation summaries
• module cards
• stable code summaries
• architecture decisions
• handoff bundles

Retrieval Ownership Split

• qmd: canonical docs and document collections
• Zvec: promoted memory objects and other non-doc artifacts
• metadata store: confidence, evidence, provenance, scope, staleness, promotion status, and sync state

This split is intentional. It prevents overlapping retrieval systems from fighting over the same job.

Reasoning Model

The target reasoning lifecycle is:

• scratch reasoning: local, bounded, disposable
• checkpoint summaries: compact recovery points
• promoted conclusions: reusable machine memory
• canonical docs: durable human truth

Hard rule:

• raw chain-of-thought is not long-term memory by default
• only promoted conclusions should become durable memory

Promotion should be gated by:

• evidence
• confidence
• stability beyond the current task
• likely future reuse

Token Management

The project should treat token limits as a first-class design problem.

Policy defaults:

• target active context ceiling: 64K
• compaction trigger example: 45K

These are engineering defaults, not universal facts. The core idea is:

• retrieve on demand
• checkpoint at subtask boundaries
• compress old context
• pass summaries and handoff bundles instead of raw transcripts

MCP Integration

MCP is the stable interface layer between the agent and the memory system.

Recommended MCP surface:

• retrieve_context
• search_docs
• search_memory
• promote_memory
• summarize_session
• generate_handoff
• map_changed_modules

The current implementation still exposes the original 12 tools. The architecture work in docs/plans/ describes how that surface should evolve.

qmd Indexing Policy

qmd indexing should remain a controlled workflow. Do not treat it like a chatty automatic hook that re-indexes on every tiny change, and do not modify qmd's DB directly. Batch or queue indexing work instead.

Cloud-Assisted, Local-First Fallback

Provider policy for the target system:

• embeddings: cloud-assisted first, local fallback
• summarization/compression: cloud-assisted first, local fallback
• retrieval: local against indexed artifacts whenever possible

This repository is being designed to work even when internet access fails.

Current Repository Layout

.
├── CLAUDE.md
├── README.md
├── docs/plans/
├── main.py
├── mcp_tools.py
├── models.py
├── session_manager.py
├── errors.py
├── memory-bank/
└── tests/

Current Server Components

• main.py: MCP entry point and tool registration
• mcp_tools.py: current business logic for exposed tools
• session_manager.py: session persistence and memory-bank file operations
• models.py: current dataclasses and enums
• errors.py: exception hierarchy

Historical Setup Note

Older docs referenced:

uv sync
uv run main.py

Use those commands only if the dependency manifest is present in your checkout. The current repository snapshot may not include pyproject.toml.

License

MIT License