Waymark

Waymark

Shared memory and handoff hub for AI agents, enabling seamless context transfer between sessions with token-budgeted resumes and automatic handoffs.

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README

Waymark

Shared memory and handoff hub for AI agents. A waymark is a trail sign left for whoever walks the path next — Waymark does the same for agent sessions: Claude Code finishes work, and the next session of Codex, Claude Desktop, or any other MCP client starts already knowing what was done, what was decided, and what to do next.

No retelling. No re-reading the repo. One token-budgeted call.

Why

Every new agent session starts cold: it re-reads files, re-asks questions, and burns tokens rediscovering context that another agent had five minutes ago. Waymark replaces that with a local MCP server over a single SQLite database shared by all your agents:

  • workspace_resume — one call returns a compact packet (project metadata, open tasks, ranked memory, recent sessions, active handoff) within a token budget you set (default 1,200 tokens).
  • Automatic handoffssession_log(outcome: "partial", next_steps: [...]) writes a handoff memory that tops the next agent's resume. Logging completed retires it. No discipline required.
  • Task queue with atomic claimstask_claim guarantees only one agent takes a task, with capability and dependency checks.
  • Memory lifecycle — supersede instead of accumulate; feedback ratings demote stale records in ranking.
  • Provider-neutral — agents register with provider/model/client identity; nothing in the core is tied to one vendor.

Measured savings

Continuation scenario (fresh session must orient in a project and name the next step), estimated cohort, reproducible via node scripts/benchmark-orientation.cjs:

median tokens
Cold orientation (reading README, docs, sources, git log) 13,540
Waymark resume (packet + core tool schemas + follow-up reads) 3,392
Net saving 74.9%

The orientation context itself shrinks from ~13.1k tokens of raw files to a 1.1k-token ranked packet (−91.5%) — and unlike cold reading, the packet contains what files can't: what the previous agent actually did and decided. The exact-token A/B protocol with live clients is in docs/BENCHMARK_RUN.md.

Quick start

Requires Node.js 22+.

git clone <this-repo> waymark && cd waymark
npm install
npm run build
npm test          # 19 integration tests

Connect Claude Code (stdio)

claude mcp add --scope user waymark node "<path-to>/waymark/dist/server.js"

Optional but recommended — auto-inject the resume packet into every new session via a SessionStart hook (zero tool calls spent on orientation), see scripts/hooks/session-start-resume.cjs.

Connect Codex

# ~/.codex/config.toml
[mcp_servers.waymark]
command = "node"
args = ["<path-to>/waymark/dist/server.js"]

Connect Claude Desktop / web (HTTP)

node dist/server.js --http   # listens on 127.0.0.1:3747

Add a custom connector: http://localhost:3747/mcp. Also available via docker compose up -d / podman compose up -d.

The protocol

Session start — one call, not three:

workspace_resume(project_id, task?, agent_id?, max_tokens=1200)

Session end:

session_log(started_at, summary, outcome, next_steps?)   # partial/blocked → auto-handoff
memory_write(...)                                        # only durable decisions/facts

Cross-agent handoff happens automatically: agent A logs a partial session with next_steps; agent B's workspace_resume surfaces that handoff first, with the session trail and files touched. When someone logs completed, the handoff retires itself.

Tool profiles

Greedy MCP clients inject every tool schema into context each turn. Waymark defaults to a core profile of 10 tools (~1.8k tokens instead of ~4.7k for all 28). Set HUB_TOOLS=full where you need the admin surface (projects, agents, experiments, telemetry).

Tools (28)

Group Tools
Context workspace_resume, context_get
Memory memory_write/read/list/search/set_status/feedback
Tasks task_create/list/update/claim/release/add_dependency
Projects project_list/get/upsert/set_status
Agents agent_register/get/list/set_status
Sessions & telemetry session_log, usage_report, experiment_create/list/update/summary

Deep dives: docs/CONTEXT.md, docs/MEMORY_LIFECYCLE.md, docs/TASK_COORDINATION.md, docs/BENCHMARKING.md.

Dashboard

npm run dashboard → read-only web panel on http://localhost:4747: projects, tasks, memory (FTS search), sessions, agents, benchmark results. Opens the DB in read-only mode — it physically cannot mutate hub state.

Architecture

src/server.ts            entry point: stdio / HTTP (--http), tool profiles
src/db/client.ts         SQLite singleton (WAL) + idempotent migrations 001..005
src/tools/               projects · memory · tasks · sessions · agents · context · telemetry
src/context/builder.ts   deterministic ranking + token budget (no LLM calls)
src/cli/benchmark.ts     A/B experiment CLI
dashboard/               read-only Express panel

Storage: SQLite + FTS5. The core never calls an LLM or any external service.

Principles

  • Context on demand — summaries + ids by default; bodies only when asked.
  • Budget first — every aggregated response fits a token budget.
  • Evidence over retelling — link files/commits/tasks instead of copying text.
  • Replace, don't accumulate — supersede outdated memory, no duplicates.
  • Provider-agnostic — any MCP client is a first-class citizen.

License

MIT

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