ccontext
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., "@ccontextget the current context and show me what tasks are active"
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.
ccontext-mcp — Execution Context for AI Agents
Local-first MCP server that gives agents a shared, durable “execution context” across sessions: Vision (why) · Sketch (static blueprint) · Milestones (timeline) · Tasks (deliverables) · Notes/Refs (knowledge) · Presence (who’s doing what).
🧠 Persistent agent memory • 📋 Agent-native task tracking • 🧹 Built-in hygiene (diagnostics + lifecycle) • ⚡ Batch updates (one call) • 🔒 Local files, zero infra
🖼️ ccontext at a Glance
Files on disk (portable, git-friendly)
your-project/
└── context/
├── context.yaml # vision, sketch, milestones, notes, references (+ embedded contract)
├── tasks/
│ ├── T001.yaml # deliverable tasks with steps
│ └── T002.yaml
├── presence.yaml # runtime status (recommend gitignore)
├── .ccontext.lock # lock file (recommend gitignore)
└── archive/ # auto-archived notes/refs/tasks (optional gitignore)One call to “load the brain”
get_context() returns version + now + diagnostics so agents can quickly orient:
{
"version": "abc123def456",
"now": {
"active_milestone": { "id": "M2", "name": "Phase 2", "description": "...", "status": "active" },
"active_tasks": [{ "id": "T001", "name": "Implement auth", "milestone": "M2" }]
},
"diagnostics": {
"debt_score": 2,
"top_issues": [{ "id": "NO_ACTIVE_MILESTONE", "severity": "info", "message": "No active milestone." }]
},
"context": { "...": "vision/sketch/milestones/notes/references/tasks_summary" }
}Why ccontext? (Pain → Payoff)
The Pain
Agents forget what they were doing between sessions.
Multi-agent work becomes N² coordination noise without a shared “source of truth”.
Context grows unbounded; old notes become misleading; task state drifts.
The Payoff
Resume instantly: agents always start from the same structured context.
Coordinate cleanly: presence shows who’s doing what; tasks show what’s actually done.
Stay sane: diagnostics highlight context debt; ttl-based lifecycle prevents bloat.
✨ What Makes ccontext Different
🗂️ Local-first, Portable
Context is plain YAML in your repo. No DB, no cloud, no lock-in.
📋 Agent-native Structure
Designed around how agents actually work: vision, blueprint, milestones, tasks, notes.
⚡ Low-friction Updatescommit_updates() batches multiple changes in one call (status + task step + note).
🧹 Context Hygieneget_context() emits diagnostics + top issues so agents know what to fix.
⏳ Lifecycle Built-in
Notes/refs decay by ttl and auto-archive, keeping context fresh.
👥 Presence That Stays Readable
Presence is normalized (single-line, de-duped) by design.
Core Model (The “Contract”)
Vision: one-sentence north star. Low frequency.
Sketch: static blueprint only (architecture, strategy, constraints, major decisions).
Do not put TODO/progress/task lists here.Milestones: coarse phases (typically 2–6). Exactly one active at a time.
Tasks: deliverables with 3–7 steps. If work spans handoffs, it belongs in a task.
Notes/References: “things we must not forget” + “where to look”.
Presence: what each agent is doing/thinking right now (keep it short).
This contract is embedded into context.yaml under meta.contract for standalone use.
Installation
Claude Code
# Using uvx (recommended)
claude mcp add ccontext -- uvx ccontext-mcp
# Or using pipx
claude mcp add ccontext -- pipx run ccontext-mcpClaude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"ccontext": {
"command": "uvx",
"args": ["ccontext-mcp"],
"env": { "CCONTEXT_ROOT": "/path/to/your/project" }
}
}
}Other MCP clients / manual
pip install ccontext-mcp
CCONTEXT_ROOT=/path/to/project ccontext-mcpRoot selection: ccontext uses CCONTEXT_ROOT when set; otherwise it uses the current working directory.
Agent Loop (Recommended)
Start every run
ctx = get_context() # call firstIf missing, set the foundation
update_vision("Ship a reliable X that achieves Y.")
update_sketch("## Architecture\n...\n## Strategy\n...\n## Risks\n...")Keep one milestone active
create_milestone(name="Phase 1: Foundation", description="...", status="active")Track real work as tasks
create_task(
name="Implement auth",
goal="Users can sign in and sessions are validated",
steps=[
{"name":"Design", "acceptance":"Spec reviewed"},
{"name":"Implement", "acceptance":"Tests passing"},
{"name":"Rollout", "acceptance":"Docs updated"}
],
milestone_id="M1",
assignee="peer-a"
)Update with low friction (one call)
commit_updates(ops=[
{"op":"presence.set","agent_id":"peer-a","status":"Auth: implementing session validation; checking edge cases"},
{"op":"task.step","task_id":"T001","step_id":"S2","step_status":"done"},
{"op":"note.add","content":"Edge case: empty header triggers fallback path","ttl":50}
])Tools
Category | Tool | Purpose |
Context |
| Call first. Returns |
| Batch multiple updates (presence + task progress + notes/refs) in one call. | |
Vision / Sketch |
| Set the north star. |
| Update blueprint (static, no TODO/progress). | |
Presence |
| See what other agents are doing. |
| Update your status (1–2 sentences). | |
| Clear your status (remove stale/finished status). | |
Milestones |
| Manage coarse phases. |
Tasks |
| Track deliverables with steps. |
Notes / Refs |
| Preserve lessons/decisions with ttl lifecycle. |
| Bookmark key files/URLs with ttl lifecycle. |
Version Tracking (ETag-style)
Agents can detect change without guessing:
v = get_context()["version"]
# ... later ...
if get_context()["version"] != v:
# someone changed context/tasks
ctx = get_context()Note: version is semantic. It intentionally ignores notes/refs ttl decay so frequent reads don’t churn the hash.
Diagnostics & Lifecycle (Context Hygiene)
Diagnostics:
get_context()returnsdiagnostics(includingdebt_scoreandtop_issues) so agents can keep the context clean.TTL-based lifecycle: notes and references decay by 1 each
get_context()call and auto-archive when stale, preventing “memory bloat”.Presence normalization: agent IDs are canonicalized and de-duped; status is normalized to a single concise line for readability.
Git Recommendations
Most teams prefer:
context/presence.yaml
context/.ccontext.lock
context/archive/Commit context/context.yaml and context/tasks/ so work survives sessions and can be reviewed.
Works With (and Without) Orchestrators
Standalone: any MCP-capable agent client can use ccontext directly.
Orchestrators: tools like CCCC can read/write the same
context/files for multi-agent runtime UX.No MCP? You can still read/write the YAML files manually (you just won’t get MCP ergonomics like batch updates and diagnostics).
License
MIT
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