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HTTP API

The CTXone Hub exposes a REST API over HTTP when run with --http. This doc lists every endpoint, its request format, response format, and any query parameters.

All endpoints live under http://<host>:<port>/api/. Default host and port: 0.0.0.0:3001. CORS is enabled with Allow-Origin: *.

  • Branch/ref parameter: most endpoints take a branch name in the URL path ({ref_name}) or as a ref query string / body field. Defaults to main.
  • Namespace parameter: every ref-touching endpoint also accepts a namespace (see Namespaces below). Defaults to default.
  • Content type: requests and responses use application/json.
  • Error responses: HTTP 4xx for bad input, 5xx for server errors. Body is plain text with a human-readable message.

A namespace isolates everything ref-scoped: branches, plans, memory (facts / pinned / primed / sessions), taints, reminders, and history. One namespace typically maps to one code repo via the project registry. Pre-existing data lives in the reserved default namespace; nothing migrates.

Every ref-touching endpoint (state/paths/search, log, blame, diff, merge, branches, memory/*, plans/*, taint/*, reminders/*, session turns) resolves its namespace the same way:

  1. ?namespace=<ns> query parameter (takes precedence)
  2. X-CTXone-Namespace: <ns> header
  3. Neither present → the default namespace

Rules:

  • Namespace names are ASCII [A-Za-z0-9_-], 1–64 bytes. An invalid name returns 400.
  • Namespaces are created by registering a project (POST /api/projects); ref operations in a namespace that doesn’t exist return 404.
  • Cross-namespace merge is deny-by-default: attempting it returns 403 (per AgentStateGraph’s isolation rules).

Simple liveness check.

Response (200):

{
"status": "ok",
"service": "ctxone-hub"
}

Used by ctx status and ctx doctor.


Cumulative token savings aggregated across every session.

Response (200):

{
"session_id": "_aggregate",
"session_tokens_used": 98,
"session_tokens_saved": 1706,
"total_graph_size_chars": 1804,
"total_graph_size_tokens": 451,
"cumulative_ratio": 18.43
}
  • session_id — always "_aggregate" to signal this is a roll-up, not a single-session snapshot
  • session_tokens_used — sum of tokens actually sent across all sessions
  • session_tokens_saved — sum of (recalls × flat_baseline) - used across all sessions
  • total_graph_size_charsmax observed across sessions (graph size is process-global, not summable)
  • total_graph_size_tokenschars ÷ 4
  • cumulative_ratio(used + saved) / used

Stats for a single logical session. session_id is whatever clients pass in the X-CTXone-Session header; absent clients roll up under "default".

Response (200):

{
"session_id": "[email protected]",
"session_tokens_used": 42,
"session_tokens_saved": 658,
"total_graph_size_chars": 1804,
"total_graph_size_tokens": 451,
"cumulative_ratio": 16.67
}

Returns 404 if the session ID has never been seen. Sessions are created lazily the first time a read endpoint (recall, context) records token usage for them.

List every known session with its current stats.

Response (200):

[
{ "session_id": "[email protected]", "session_tokens_used": 42, "session_tokens_saved": 658, "total_graph_size_chars": 1804, "total_graph_size_tokens": 451, "cumulative_ratio": 16.67 },
{ "session_id": "[email protected]", "session_tokens_used": 120, "session_tokens_saved": 1200, "total_graph_size_chars": 1804, "total_graph_size_tokens": 451, "cumulative_ratio": 11.00 },
{ "session_id": "default", "session_tokens_used": 0, "session_tokens_saved": 0, "total_graph_size_chars": 1804, "total_graph_size_tokens": 451, "cumulative_ratio": 0.0 }
]

Sorted by session_id. The "default" session is always present even on a fresh Hub.

Record one LLM turn’s token usage against the caller’s session. Agents call this after each significant LLM turn with numbers copied straight from the provider response’s usage field. Returns the updated SessionSnapshot so callers see running totals in one round trip.

The session is resolved via X-CTXone-Session (same mechanism as every other endpoint). Unknown sessions are auto-created.

Request body:

{
"input_tokens": 2400,
"output_tokens": 450,
"cache_read_tokens": 1800,
"cache_create_tokens": 600,
"model": "claude-sonnet-4.5",
"provider": "anthropic"
}
  • input_tokens (required) — fresh input tokens the model consumed, NOT counting anything served from cache. Report input disjoint from cache_read_tokens (see the note below).
  • output_tokens (required) — tokens the model generated
  • cache_read_tokens — tokens served from the prompt cache, default 0
  • cache_create_tokens — tokens written to the prompt cache (Anthropic prompt caching), default 0
  • model — human-readable model identifier for display, optional
  • provider — provider identifier (anthropic, openai, gemini, …), optional

All token fields are u64; negative or malformed values are rejected by the JSON parser.

Cached tokens must not be double-counted. CTXone treats the four fields as disjoint — the total for a call is input + output + cache_read + cache_create. Anthropic already reports input this way (its input_tokens excludes cache reads). OpenAI / Codex do not: their input_tokens includes the cached portion (cached_input_tokens is a subset), so a raw copy would count the cached tokens in both input and cache_read. Subtract the cached count from input before reporting: input = input_tokens − cached_input_tokens. Getting this wrong inflates the token total (~2× on cache-heavy sessions) and overcharges cost, since the cached tokens would be priced at the full input rate instead of the cache-read rate.

Response (200):

{
"session_id": "[email protected]",
"session_tokens_used": 12,
"session_tokens_saved": 340,
"total_graph_size_chars": 1804,
"total_graph_size_tokens": 451,
"cumulative_ratio": 29.33,
"llm_input_tokens": 2400,
"llm_output_tokens": 450,
"llm_cache_read_tokens": 1800,
"llm_cache_create_tokens": 600,
"llm_call_count": 1,
"last_model": "claude-sonnet-4.5",
"last_provider": "anthropic"
}

Error responses:

  • 400 Bad Request (or 422 Unprocessable Entity, depending on axum’s extractor) when input_tokens or output_tokens are missing, non-numeric, or negative.

Recall integration: once a session has reported LLM usage at least once, every subsequent GET /api/memory/recall from the same session carries a session_llm_stats sub-object so agents see the running totals alongside the results:

{
"results": [...],
"ctx_tokens_sent": 300,
"ctx_tokens_estimated_flat": 1500,
"ctx_savings_ratio": 5.0,
"pinned_count": 2,
"topic_matches": 3,
"session_llm_stats": {
"input_tokens_total": 12500,
"output_tokens_total": 3200,
"cache_read_tokens_total": 8900,
"cache_create_tokens_total": 450,
"call_count": 17
}
}

The field is only present for sessions that have reported usage — sessions that haven’t see the same shape they’ve always seen.

Recompute each session’s per-model token split from its stored per-turn snapshots, and replace the stored split with the result. Every turn at /sessions/{id}/turns/{idx} already carries its own model and tokens, so this recomputes the per-model breakdown without re-ingesting (no double-counting) and without touching the graph (no memory loss). It is idempotent — running it again yields the same replacement. Scoped to the request namespace (X-CTXone-Namespace).

Use it after importing sessions recorded before the per-model split existed, or any time a session’s per-model numbers look wrong.

Cached-token normalization. As it recomputes, the backfill enforces the disjoint-fields rule above: for OpenAI / Codex-family models (gpt-*, codex*, o1/o3/o4) it subtracts the cached count from input (input = input_tokens − cache_read), since those providers fold cached tokens into input_tokens. Anthropic turns are left as-is. This is why recomputing is the right fix for historical Codex sessions whose totals were inflated — it happens at aggregation, so stored turns keep their provider-native shape and re-running stays idempotent.

Two modes:

  • One session — pass ?session=<id> to recompute just that session. This is what ctx ingest-session calls after writing a session’s turns, so a re-ingest never inflates the split. Always fast.
  • Whole namespace — omit session to walk every session. The walk is bounded per request so it can never exceed the HTTP timeout, no matter how large the namespace’s database is.

Query parameters (whole-namespace mode):

  • max_secs — soft wall-clock budget in seconds, default 20. The walk stops once the budget elapses (after finishing the in-flight session) and returns a cursor. 0 is treated as 1, and at least one session is always processed so a spent budget can’t stall.
  • limit — optional hard cap on how many sessions this request processes, applied on top of the time budget.
  • offset — resume cursor: skip this many sessions (in sorted order) before processing. Pass back the next_offset from the previous response.

Response (200):

{
"status": "ok",
"namespace": "default",
"sessions_updated": 25,
"turns_scanned": 4820,
"models": ["claude-opus-4-8", "gpt-5.2-codex"],
"total": 60,
"processed": 25,
"next_offset": 25,
"done": false
}
  • total — sessions in the namespace
  • processed — sessions handled this request
  • sessions_updated — of those, how many had turns to recompute from (a session with no stored turns is left untouched)
  • next_offset — where to resume, or null when finished
  • donetrue once every session has been processed

Draining a large namespace. Loop, passing back the cursor, until done is true:

Terminal window
offset=0
while :; do
resp=$(curl -s -X POST \
"http://localhost:3001/api/stats/backfill_by_model?offset=$offset" \
-H "X-CTXone-Namespace: default")
echo "$resp"
[ "$(echo "$resp" | jq -r .done)" = "true" ] && break
offset=$(echo "$resp" | jq -r .next_offset)
done

Turn-less sessions. Backfill only replaces a session’s split when it finds stored turns to recompute from — a session with none is left as-is. If such a session’s stored numbers are wrong, backfill cannot fix them; delete the session (DELETE /api/sessions/{sid}) instead.

Structural stats for a branch.

Response (200):

{
"commit_count": 27,
"path_count": 21,
"branch_count": 2,
"epoch_count": 0,
"agents": ["ctxone", "ctxone-prime"],
"categories": ["Checkpoint", "Custom(\"Observe\")"],
"latest_commit": {
"id": "sg_e762325fed96",
"timestamp": "2026-04-14T17:47:43Z",
"agent": "ctxone",
"intent": "fact description"
}
}

A hub-global rollup with one entry per workspace (namespace) — the data behind the Hub Home overview. One call returns token and graph aggregates for every workspace, so the dashboard needs no per-workspace fan-out. Short-TTL cached (~15s) since it walks every namespace.

Response (200):

{
"workspaces": [
{
"namespace": "default",
"session_count": 153,
"representative_model": "gpt-5.2",
"tokens": {
"used": 1700,
"saved": 5200,
"llm_input": 5100000000,
"llm_output": 27100000,
"llm_cache_read": 7500000000,
"llm_cache_create": 69500000,
"by_model": {
"claude-opus-4-8": { "input_tokens": 126025, "output_tokens": 1781988, "cache_read_tokens": 754047192, "cache_create_tokens": 36456103, "call_count": 214 },
"gpt-5.4": { "input_tokens": 2497100792, "output_tokens": 6201704, "cache_read_tokens": 2373367552, "cache_create_tokens": 0, "call_count": 1412 }
}
},
"graph": { "commit_count": 10000, "path_count": 10000, "branch_count": 41, "epoch_count": 0 }
}
]
}
  • representative_model — the workspace’s most-common last_model, used only as a label.
  • tokens.llm_* — the four token classes summed across the workspace’s sessions.
  • tokens.by_model — the same totals split per model (each entry is a ModelUsage, as in GET /api/stats/sessions).

Cost is priced per model. The Hub Home cost tile sums each model’s tokens at that model’s own rate (input + output + cache-read + cache-write), then adds the per-model costs — the same basis as the workspace LLM-usage panel. Pricing the whole workspace at a single representative model would mis-price a mixed-model workspace: one that is mostly Opus but whose most-common model is a cheaper model would read far too low. by_model is what makes the accurate, per-model figure possible; representative_model is kept only for the label. (Older hubs that predate by_model fall back to the single-model estimate.)


Read a value at a specific path.

Query params:

  • path — JSON path to read (default: /)

Response (200): the value at that path, pretty-printed JSON.

GET /api/state/{ref_name}/paths?prefix=<prefix>&max_depth=<n>

Section titled “GET /api/state/{ref_name}/paths?prefix=<prefix>&max_depth=<n>”

List all paths under a prefix.

Query params:

  • prefix — path prefix (default: /)
  • max_depth — max tree depth (default: 50)

Response (200): array of path strings.

["/memory/licensing/abc", "/memory/architecture/def", ...]

GET /api/state/{ref_name}/search?query=<q>&max_results=<n>

Section titled “GET /api/state/{ref_name}/search?query=<q>&max_results=<n>”

Literal substring search across values and keys.

Query params:

  • query — substring to match (case-insensitive)
  • max_results — max results (default: 50)

Response (200):

[
{"path": "/memory/licensing/abc", "value": "CTXone uses BSL-1.1"},
...
]

Recent commit history.

Query params:

  • limit — max commits (default: 20)

Response (200): array of commits. See the log response schema in CLI_REFERENCE.md.

Provenance chain for a specific path.

Query params:

  • path — path to blame

Response (200): array of blame entries with commit id, agent, timestamp, intent, and confidence.

Diff two refs.

Query params:

  • ref_a — first ref (usually older / base)
  • ref_b — second ref (usually newer / target)

Response (200):

{
"ref_a": "main",
"ref_b": "experiment",
"ops": [
{"op": "AddKey", "path": "/memory/test", "key": "abc", "value": "..."},
{"op": "SetValue", "path": "/...", "old": {...}, "new": {...}},
{"op": "RemoveKey", "path": "/...", "key": "..."}
]
}

Op tags: SetValue, AddKey, RemoveKey, AppendItem, RemoveItem.


List all branches.

Response (200):

[
{"name": "main", "id": "sg_e762..."},
{"name": "experiment", "id": "sg_a3b1..."}
]

Create a new branch.

Request body:

{
"name": "experiment",
"from": "main",
"if_missing": false,
"git_branch": "feature/experiment"
}
  • name (required) — branch to create
  • from — ref to branch from (default main)
  • if_missing — idempotent ensure: an already-existing branch is success, not an error (default false). Branch mirroring re-ensures on every CLI invocation with this flag.
  • git_branch — optional raw git branch this ASG branch mirrors. Recorded once, on actual creation, as metadata at /ctxone/branches/<name>/git_branch on the from ref (sanitization is lossy: feature/xfeature-x).

Response (200):

{
"status": "ok",
"name": "experiment",
"from": "main",
"existed": false,
"commit_id": "sg_a3b1..."
}

existed is true when if_missing was set and the branch already existed (in which case commit_id is omitted).


A project maps a code repo to an ASG namespace. The registry lives in the Hub’s sqlite database (projects and project_paths tables) — memory/postgres backends have no registry, so project endpoints return 400 there. Registered projects are what the CLI and MCP server use to auto-detect the namespace from a working directory.

List registered projects.

Response (200):

[
{
"id": "myrepo",
"remote_url": "https://github.com/alice/myrepo",
"namespace": "myrepo",
"display_name": "My Repo",
"created_at": "2026-07-01T12:00:00Z",
"local_paths": ["/home/alice/myrepo"],
"asd_repos": ["myrepo"]
}
]

asd_repos lists the pool-managed ASD repos whose db path lives under one of the project’s local_paths. The binding is derived, not stored — registering an ASD repo under a project’s path is what binds it.

Register a project and create + initialize its ASG namespace (idempotent — the namespace gets an initialized main branch so ref operations work immediately).

Request body:

{
"id": "myrepo",
"remote_url": "https://github.com/alice/myrepo",
"namespace": "myrepo",
"display_name": "My Repo",
"local_path": "/home/alice/myrepo"
}
  • id (required) — project id (kebab-case). Doubles as the namespace name unless namespace is given.
  • remote_url — git remote for detection. Normalized on write: trailing .git and / are stripped.
  • namespace — explicit namespace name (default: the id)
  • display_name — human-readable name
  • local_path — checkout path to bind

Response (200): the project object (same shape as GET /api/projects entries). Returns 409 on a duplicate id or remote_url, 400 on an invalid namespace name.

Fetch one project. 404 if the id is unknown.

Bind another local checkout to the project.

Request body: { "local_path": "/home/alice/myrepo-worktree" }

Response (200): the updated project object. 404 if the id is unknown.

Run the detection chain for a directory and report which namespace a session started there would land in:

  1. .ctxproject file (first non-empty line = project id) in cwd or any parent
  2. git remote get-url origin looked up in the registry (URLs normalized the same way as on write)

Response (200):

{ "status": "found", "via": "ctxproject", "project_id": "myrepo", "namespace": "myrepo" }

via is "ctxproject" or "remote" (remote matches also carry remote_url). No match:

{ "status": "not_found", "namespace": "default" }

Non-sqlite backends report { "status": "registry_unavailable", "namespace": "default" }.


These are the endpoints CTXone’s memory layer adds on top of the underlying state primitives.

Store a fact.

Request body:

{
"fact": "CTXone uses BSL-1.1 licensing",
"importance": "high",
"context": "licensing",
"tags": ["legal", "decision"],
"ref": "main"
}
  • fact (required) — the string to store
  • importancehigh / medium / low (default medium). Maps to confidence 0.95/0.7/0.4.
  • context — category name; storage path is /memory/<context>/<id>
  • tags — queryable tags stored on the commit
  • ref — branch to write to (default main)

Response (200):

{
"status": "ok",
"ref": "main",
"path": "/memory/licensing/18a6...",
"commit_id": "sg_e762..."
}

Delete a memory at a specific path.

Request body:

{
"path": "/memory/licensing/18a6...",
"reason": "superseded by new policy",
"ref": "main"
}

Marked in blame as a Rollback intent with the given reason.

Response (200):

{
"status": "ok",
"ref": "main",
"path": "/memory/licensing/18a6...",
"commit_id": "sg_next..."
}

GET /api/memory/recall?topic=<t>&budget=<n>&ref=<r>

Section titled “GET /api/memory/recall?topic=<t>&budget=<n>&ref=<r>”

Retrieve memories for a topic. Pinned-first, token-scored, budget-capped.

Query params:

  • topic — query string (tokenized, multi-word supported)
  • budget — max token budget (default 1500)
  • ref — branch (default main)

Response (200): see the recall response schema in CLI_REFERENCE.md.

Every recall updates the session token counters — each call’s sent contributes to session_tokens_used on GET /api/stats/tokens.

Load the full context tree for a project.

Response (200):

{
"project": "myproject",
"ref": "main",
"context": {
"status": "active",
"decisions": {...}
},
"ctx_tokens_sent": 234,
"ctx_tokens_estimated_flat": 1191
}

Load structured sections as pinned or searchable memory.

Request body:

{
"source": "project",
"pinned": true,
"sections": [
{"title": "The Insight", "body": "..."},
{"title": "The Roadmap", "body": "..."}
],
"ref": "main"
}
  • source (required) — group name; re-priming the same source overwrites
  • pinned — if true, always include in recall; otherwise searchable (default false)
  • sections — parsed markdown sections from the client
  • ref — branch (default main)

Response (200):

{
"status": "ok",
"ref": "main",
"source": "project",
"pinned": true,
"sections_written": 5,
"paths": [
"/memory/pinned/project/the-insight",
"/memory/pinned/project/the-roadmap",
...
]
}

List all pinned memories.

Response (200):

[
{"path": "/memory/pinned/project/the-insight/title", "value": "The Insight"},
{"path": "/memory/pinned/project/the-insight/body", "value": "..."},
...
]

Clients typically group these by /memory/pinned/<source>/<slug> and pair the /title and /body children to reconstruct structured sections. Returns an empty array (not 404) when no pinned memories exist.

End-of-session commit capturing what was learned.

Request body:

{
"session_id": "2026-04-14-afternoon",
"key_points": ["Shipped Postgres backend", "Built auth middleware"],
"decisions": ["SaaS as on-ramp", "agent memory is top priority"]
}

Response (200):

{
"status": "ok",
"session_id": "2026-04-14-afternoon",
"key_points": 2,
"decisions": 2
}

GET /api/memory/what_changed_since?since=<iso>

Section titled “GET /api/memory/what_changed_since?since=<iso>”

Recent commits filtered to those after a timestamp.

Query params:

  • since — ISO 8601 timestamp (e.g., 2026-04-12T00:00:00Z)

Response (200): array of commit summaries.

GET /api/memory/why_did_we?decision=<text>

Section titled “GET /api/memory/why_did_we?decision=<text>”

Search for a decision and return its blame chain.

Query params:

  • decision — substring of the decision to look up

Response (200):

{
"decision": "use BSL-1.1",
"traces": [
{
"path": "/memory/licensing/abc",
"blame": [...]
}
]
}

StatusMeaningExample body
400Malformed request (missing required field, invalid namespace name)"missing field \fact`”`
403Cross-namespace merge denied"cross-namespace merge denied: ..."
404Path, ref, or namespace not found"ref not found: experiment"
409Conflict (duplicate project id / remote_url)"UNIQUE constraint failed: projects.id"
500Internal error (storage, engine)"tree error: ..."

The body is plain text, not JSON. Clients should log and retry on 5xx.


The Hub enforces a per-peer-IP token-bucket rate limit in HTTP mode. Default: 600 requests/minute per IP (permissive — catches runaway loops without bothering real agents).

Clients that exceed the bucket get:

HTTP/1.1 429 Too Many Requests
Retry-After: 3
X-RateLimit-Limit: 600
X-RateLimit-Remaining: 0

Configure via --rate-limit-rpm <N> or the CTXONE_RATE_LIMIT_RPM env var. 0 disables rate limiting entirely. See docs/TROUBLESHOOTING.md#rate-limiting for details.

Send X-CTXone-Session: <id> on any request to have its token usage counted under that session. Absent the header, usage rolls up under the "default" session. Per-session stats are exposed via:

  • GET /api/stats/tokens/{session_id} — single-session snapshot
  • GET /api/stats/sessions — all sessions
  • GET /api/stats/tokens — cross-session aggregate (backward-compat)

The Python client accepts a session_id constructor arg or reads CTX_SESSION_ID from the environment.

Send X-CTXone-Agent: <name> on any write request (remember/forget/prime/summarize_session/merge) to stamp the commit with that agent ID. ctx blame and /api/log/{ref} responses surface this as agent_id, so you can tell which tool wrote each fact.

Absent the header, commits are attributed to "ctxone". The Python client accepts an agent_id constructor arg or reads CTX_AGENT_ID from the environment; the Hub binary accepts --agent-id <name> for MCP stdio mode (which is what ctx init wires into the generated .mcp.json / .cursor/mcp.json etc).

See docs/TROUBLESHOOTING.md#per-tool-agent-ids for the full resolution order and examples.

All plan endpoints live under /api/plans/* and honor X-CTXone-Agent for blame attribution + X-CTXone-Session for stats. A ref query parameter selects the branch (default main).

Create a plan.

POST /api/plans
{
"name": "website-v2",
"description": "Brand pivot",
"ref": "main"
}
→ 201 Created
{
"name": "website-v2",
"description": "Brand pivot",
"status": "active",
"created_by": "claude-code",
"created_at": "2026-04-16T…",
"task_counts": { "pending": 0, "in_progress": 0, "done": 0, "abandoned": 0, "total": 0 }
}
→ 409 Conflict (plan already exists)

List plans on a branch, optionally filtered by status. Response body is a JSON array of plan objects.

Fetch one plan with its full tasks[] list.

Remove a plan destructively. Use POST /api/plans/{name}/archive for a soft, reversible alternative.

Add a task. Body fields:

FieldTypeRequired
titlestringyes
descriptionstringno
prioritylow/medium/high/criticalno
parent_idstringno (subtask support)
assigned_tostringno — agent id
blocked_bystring[]no
refstringno

Returns the created task on 201.

List tasks in a plan, flat.

GET /api/plans/{name}/tasks/{task_id}?ref=main

Section titled “GET /api/plans/{name}/tasks/{task_id}?ref=main”

Fetch a single task.

POST /api/plans/{name}/tasks/{task_id}/start

Section titled “POST /api/plans/{name}/tasks/{task_id}/start”

Transition pending → in_progress. Returns the updated task. Returns 409 Conflict if blockers aren’t done.

POST /api/plans/{name}/tasks/{task_id}/complete

Section titled “POST /api/plans/{name}/tasks/{task_id}/complete”

Transition in_progress → done with a proof:

{ "proof": { "kind": "commit", "value": "ef6ce63" } }

Proof kind is one of commit / file / test / text. Returns 400 Bad Request when the proof value is empty or the kind is unknown.

POST /api/plans/{name}/tasks/{task_id}/abandon

Section titled “POST /api/plans/{name}/tasks/{task_id}/abandon”

Body: { "reason": "superseded" }. Reason is required (empty reasons return 400).

Soft-archive a plan.

GET /api/plans/{name}/next?ref=main&assigned_to=me&include_unassigned=true&assigned_only=false

Section titled “GET /api/plans/{name}/next?ref=main&assigned_to=me&include_unassigned=true&assigned_only=false”

Return the highest-priority pickable task wrapped as { "task": { … } } or { "task": null }. Pass assigned_to=me to filter to tasks assigned to the agent carried by X-CTXone-Agent — this is the state-driven orchestration primitive.


Completing a plan automatically seals a per-workspace epoch — a tamper-evident, point-in-time snapshot of the workspace’s memory graph at plan close. These endpoints view and download them.

One-time retroactive seal of an epoch for every already-Completed plan in the workspace, so existing workspaces show checkpoints without waiting to re-close plans. Idempotent (skips plans already sealed); safe to re-run. Scoped to the request namespace (X-CTXone-Namespace).

Response (200):

{ "status": "ok", "namespace": "default", "sealed": 12, "already_sealed": 0, "failed": 0 }

The sealed checkpoints for this workspace, newest-sealed first. Pass ?all=true for the hub-wide view (every workspace, each row tagged with its namespace).

Response (200):

{
"epochs": [
{
"id": "plan:default:website-v2",
"namespace": "default",
"plan": "website-v2",
"status": "Sealed",
"created_at": "2026-08-25T04:44:52Z",
"sealed_at": "2026-08-25T19:30:43Z",
"commit_count": 14577
}
]
}
  • id — the epoch id, plan:<namespace>:<plan-id>.
  • plan — the plan whose completion sealed it.
  • commit_count — the number of commits captured in the seal (sealed_commits).

ASG epochs live in one global table, so the Hub attributes each to its workspace by the plan:<namespace>: id prefix.

Download one sealed epoch’s audit bundle (epoch metadata + the sealed-commit manifest) as a JSON attachment. Pass the epoch’s own namespace via ?namespace=<ns>.

Terminal window
curl -OJ "http://localhost:3001/api/epochs/plan:default:website-v2/export?namespace=default"

Returns Content-Disposition: attachment so a browser download works; the id must be a plan: epoch, or the request is rejected (400), and an unknown id returns 404.


Pull-based scheduling. All reminder endpoints live under /api/reminders/*. Reminders are persisted to SQLite (same database as memory).

Create a reminder.

POST /api/reminders
X-CTXone-Agent: claude-code
{
"title": "Check feature flag rollout",
"instructions": "Query the metrics dashboard and report adoption %.",
"due_at": "2026-05-10T09:00:00Z",
"priority": "medium",
"autonomous": false
}

→ 201 Created with the reminder JSON.

List reminders. Accepts query params: status, priority_at_most, created_by, due_before, ref_id, tags.

Return all actionable reminders (due or awaiting_permission), ordered by priority. Lazily promotes pending reminders whose due_at has passed.

Get a single reminder by id.

Defer to a later time. Body: { "until": "<ISO 8601>" }.

Approve a non-autonomous reminder. Body: { "approved_by"?: "..." }.

Cancel permanently.

Mark in-progress. Body: { "agent_id"?: "..." }.

Record execution outcome. Body: { "result": "success|failed|deferred|snoozed|cancelled", "notes"?: [...], "task_id"?: "...", "agent_id"?: "..." }.


The HTTP API currently has no authentication. Run the Hub on a trusted network (loopback, VPN, or private subnet) or put a reverse proxy in front with whatever auth layer you already use.

Multi-tenant auth is tracked as future work — see the engine’s agentstategraph-mcp binary, which supports --auth and --keys-file for tenant isolation. CTXone Hub doesn’t currently expose these.