Waymark
Waymark is a shared memory and handoff hub for AI agents, enabling seamless context transfer and task coordination across sessions via a local MCP server backed by SQLite.
Resume a workspace session (
workspace_resume): Restore compact, token-budgeted project state (metadata, open tasks, ranked memories, active handoffs) for a new agent session — reducing orientation context by ~91.5% vs. cold reading.Get task-specific context (
context_get): Build focused, deterministically ranked project context tailored to a specific task, filtered by memory types and constrained to a token budget.Write & manage memory nodes (
memory_write,memory_read,memory_search): Create, read, search, and update named memory records (decisions, handoffs, references, feedback, etc.) with lifecycle statuses (active, superseded, stale, archived), confidence/importance ratings, and supersession of old records.Coordinate tasks (
task_create,task_list,task_update,task_claim): Create tasks with priorities, dependencies, and required capabilities; list/update them; and atomically claim pending tasks — ensuring only one agent takes a task after validating capabilities and resolved dependencies.Log sessions (
session_log): Record session outcomes (completed, partial, blocked) with summaries, decisions, commits, and files touched. Partial/blocked sessions automatically create handoff memories so the next agent can resume without retelling.Register agents: Agents can register themselves with provider/model/client identity for tracking.
Manage projects: List, get, upsert, and set the status of projects to organize work.
Monitor usage & experiments: Log usage reports and manage experiments, including creation, listing, updating, and summarizing results.
Dashboard: A read-only web panel to view projects, tasks, memory, sessions, agents, and benchmark results.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@WaymarkResume my workspace for project 'doc-bot'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 handoffs —
session_log(outcome: "partial", next_steps: [...])writes a handoff memory that tops the next agent's resume. Loggingcompletedretires it. No discipline required.Task queue with atomic claims —
task_claimguarantees 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.
Related MCP server: Shared Memory MCP Server
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+.
npm install -g waymark-hub
waymark-hub init # registers the hub in Claude Code / Codex, offers the hook
waymark-hub doctor # verifies the whole installationinit asks before touching anything; init --yes enables everything
applicable. The database lives in ~/.waymark/hub.db (survives package
upgrades); override with WAYMARK_HOME or DB_PATH.
From source instead:
git clone https://github.com/SerjMihashin/waymark && cd waymark
npm install && npm test # build + 20 integration testsConnect Claude Code (stdio)
waymark-hub init --claude, or manually:
claude mcp add --scope user waymark node "<install>/dist/server.js"Optional but recommended — waymark-hub init --hook installs a SessionStart
hook that injects the resume packet into every new session (zero tool calls
spent on orientation).
Connect Codex
waymark-hub init --codex, or manually:
# ~/.codex/config.toml
[mcp_servers.waymark]
command = "node"
args = ["<install>/dist/server.js"]Connect Claude Desktop / web (HTTP)
waymark-hub serve --http # listens on 127.0.0.1:3747Add 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/factsCross-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 |
|
Memory |
|
Tasks |
|
Projects |
|
Agents |
|
Sessions & telemetry |
|
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 panelStorage: 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
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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