mcpstate
Durable, user-keyed state management for stateless MCP servers. Enables agents to persist and resume state across conversations, clients, and devices.
README
mcpstate
Durable, user-keyed state for stateless MCP servers.
State that follows the user, not the session.
mcpstate gives MCP agents state that survives the end of a conversation —
and a switch to a different client, or a move to a different device. It ships as
a Python library plus a ready-to-run MCP server. Start a research session in
Claude Desktop on your laptop; continue it tomorrow from Claude Code, or from
your phone.
See it work
The demonstration below is real. Each step is a separate operating-system
process calling the actual MCP tools, sharing one on-disk backend — so the
state surviving between steps is genuine durability, not a mock. Reproduce it
with examples/research_assistant.py; full
walkthrough in docs/use-case.md.
A new conversation the next day recovers exactly where you left off:

Two devices editing at once — the conflict becomes a merge the agent performs, and no write is lost:

Why this exists
The MCP specification revision of 2026-07-28 made the protocol stateless:
Mcp-Session-Id, the initialize handshake, and SSE resumability were all
removed (changelog,
announcement).
Sessions fought load balancers; the spec chose horizontal scale.
The spec's official answer for stateful servers is the handle pattern: mint
an explicit handle (a basket_id, a research_id) from a tool, and have the
model pass it back as an ordinary argument. How a server persists what a
handle points to is explicitly out of scope — so every stateful MCP server now
needs a durable, user-scoped, expiring handle store, and nothing standardizes
one. mcpstate is that store.
What you can build with it
Any agent whose work is worth keeping between turns:
| You're building | The state that persists |
|---|---|
| A research assistant | collected sources, notes, an evolving outline |
| A shopping / ordering agent | the cart, across laptop and phone |
| A trip planner | an itinerary that grows over days |
| A writing tool | drafts and revisions |
| A tutor | a learner's progress and history |
| A long-running ops workflow | a migration checklist worked over days |
The three axes of continuity all fall out of one idea — state keyed by the user, not the connection:
flowchart LR
subgraph a [Mon · laptop]
A[Claude Desktop]
end
subgraph b [Tue · laptop]
B[Claude Code]
end
subgraph c [Tue night · phone]
C[Claude app]
end
A -- "research_k3v9x2mq" --> S[(mcpstate)]
S -- resume --> B
B -- save --> S
S -- resume --> C
| Axis | Scenario | Backend |
|---|---|---|
| Across conversations | context filled up; the next chat resumes the work | SQLite (default) |
| Across clients | started in Claude Desktop, continued in Claude Code / Cursor | SQLite (default) |
| Across devices | laptop to phone, desk to server | Redis (shared) |
Quickstart — end users (the flagship server)
One config entry gives every agent you run durable memory:
pip install "mcpstate[fastmcp]"
{
"mcpServers": {
"state": { "command": "mcpstate", "args": ["serve"] }
}
}
The server exposes six tools, written to be driven by a model:
| Tool | What the agent uses it for |
|---|---|
state_save |
Create durable state (mints a handle) or update it (versioned) |
state_load |
Load state by handle (optionally just a subtree via path) |
state_list |
"What was I working on?" — list this user's handles |
state_patch |
Additive edits where every writer lands (append, set key, merge) |
state_touch |
Renew a TTL before it expires, or make state persistent |
state_delete |
Permanently remove state |
For cross-device reach, point every device at a shared Redis:
{ "args": ["serve", "--backend", "redis://your-redis-host:6379/0"] }
Quickstart — server authors (the library)
pip install mcpstate
from mcpstate import HandleStore, Append, StaleWrite
store = HandleStore.from_url() # default: sqlite:///~/.mcpstate/state.db
# Mint: create durable state, get back an opaque handle for the model to carry.
handle = store.mint("research", {"sources": [], "notes": ""}, user="alice", ttl_days=7)
# Read: state plus the freshness metadata you need to write it back.
snap = store.get(handle, user="alice")
# Versioned save: declare which version you read. If another session wrote in
# between, you get a StaleWrite carrying the current state — hand it to your
# model to merge and retry.
try:
store.save(handle, {**snap.state, "notes": "arm64 wins"}, user="alice",
expect_version=snap.version, writer="laptop/claude-code")
except StaleWrite as conflict:
current = conflict.details["current"] # full current snapshot, agent-legible
# Commutative patch: additive edits skip version checks entirely — two devices
# appending at the same moment both land.
store.patch(handle, [Append("sources", "https://arxiv.org/abs/...")],
user="alice", writer="phone/claude")
# Renew the TTL from now — do this before it elapses; expired state is gone.
store.touch(handle, user="alice", ttl_days=7)
# Resume, any session later: what was this user working on?
for info in store.list("alice", kind="research"):
print(info.handle, info.updated_at, info.last_writer)
Async server? AsyncHandleStore mirrors every method with the same semantics,
running each call in a worker thread so backend I/O never blocks your event
loop: store = AsyncHandleStore.from_url(); await store.get(handle, user=...).
The conflict model
mcpstate implements hand-off sync: state moves between sessions like a
relay baton — one active writer at a time is the expected case, and the rare
overlap is detected and surfaced, never silently clobbered.
The design bet: your client is an LLM. Traditional sync needs CRDTs because their clients can't reason about a conflict. An agent can. A losing write gets back a structured rejection containing the winner's state and an instruction to re-read and re-apply — and the model performs a semantic merge:
sequenceDiagram
participant L as Laptop agent
participant S as mcpstate
participant P as Phone agent
L->>S: get(handle) -> version 4
P->>S: get(handle) -> version 4
P->>S: save(state', expect_version=4)
S-->>P: ok, now version 5
L->>S: save(state'', expect_version=4)
S-->>L: StaleWrite: modified by phone, now v5, here is the current state
L->>L: merge intent with phone's state
L->>S: save(merged, expect_version=5)
S-->>L: ok, now version 6
Three mechanisms, cheapest first:
- Versioned saves — every snapshot carries a version;
savedeclares the version it read; a mismatch raisesStaleWritewith the current snapshot. - Commutative patches —
Append/SetKey/DelKey/Mergeapply without version checks, so every writer's patch lands and a patch never sees aStaleWrite. Most agent-state mutations are additive, so most writes never see a conflict at all. (Precisely:Appendis fully conflict-free; two sessionsSetKey/Merge-ing the same key resolve last-write-wins for that key — the freshness metadata shows who won.) - Freshness metadata — every read returns version,
updated_at, andlast_writer, so a resuming session knows what changed while it was away.
See docs/concepts.md for the relay-baton model, why hand-off (not CRDTs) is the right v1, and the honest limits.
Backends
flowchart TD
T[flagship server tools] --> HS[HandleStore]
LIB[your server's own tools] --> HS
HS --> B{backend URL}
B -- "sqlite:///..." --> SQ[(SQLite · one machine, zero config)]
B -- "redis://..." --> RD[(Redis · shared, cross-device)]
| SQLite (default) | Redis | |
|---|---|---|
| URL | sqlite:///~/.mcpstate/state.db |
redis://host:6379/0 |
| Reach | one machine: conversations + clients | anywhere the Redis is reachable |
| Setup | none | pip install "mcpstate[redis]" + a Redis |
| Concurrency | atomic compare-and-swap via SQL, one WAL connection per thread | optimistic WATCH/MULTI transactions |
One durability note: Redis persistence is what your Redis is configured for —
with default snapshotting, a crash can lose the last seconds of writes. For
state you cannot afford to replay, enable AOF (appendfsync everysec or
stricter) on the Redis you point at.
Four environment variables configure it: MCPSTATE_BACKEND (backend URL, or
--backend), MCPSTATE_USER (identity for local/stdio; remote servers resolve
the OAuth subject instead), MCPSTATE_WRITER (the last_writer label;
defaults to hostname), and MCPSTATE_MAX_STATE_BYTES (per-handle state cap;
default 1 MiB).
Results & credibility
Everything below is reproducible from a clean checkout with python3 -m pytest.
- 117 tests, green on Python 3.11 through 3.14 in CI — with
ruffand a cleanmypy --strictpass on every push. - One backend contract suite runs against both SQLite and Redis, so the two backends are held to identical semantics — not tested separately and hoped to match.
- Concurrency is proven, not assumed. Threaded race tests assert exactly one writer wins a contended save while every commutative patch lands; the CAS engine was verified correct across separate OS processes on one WAL file. Under a 64-way patch contention stress test: 0 lost writes, 0 spurious failures (3,200 concurrent patches, all landed).
- Hardened against an adversarial review. Four independent reviewers attacked user isolation, injection/resource-exhaustion, concurrency, and API contracts. The core CAS engine and user-scoping were confirmed sound; every real finding was fixed with a regression test — HTTP fail-closed identity, issuer-scoped users, TTL-overflow and input validation, credential redaction, a 1 MiB state guard, and agent-legible structured errors on every failure path.
- Zero required dependencies in the core library (
redisandfastmcpare optional extras); shipspy.typed.
Security defaults worth knowing: state is capped at 1 MiB (configurable via
MCPSTATE_MAX_STATE_BYTES or from_url(..., max_state_bytes=...); oversized
saves return a structured state_too_large), credentials never appear
in error messages, and mcpstate serve --transport http fails closed — it
refuses unauthenticated callers unless you pass --allow-anonymous, so a
misconfigured server can't silently merge every user's state. Multi-user
identity comes from FastMCP OAuth (issuer-scoped).
API reference
HandleStore
| Method | Behavior | Raises |
|---|---|---|
from_url(url=None, *, max_state_bytes=1 MiB) |
Construct from a backend URL; None uses the SQLite default |
ValueError, BackendError |
mint(kind, state, *, user, ttl_days=None, writer=None) -> str |
Create state, return opaque handle {kind}_{8 chars} |
ValueError, StateTooLarge |
get(handle, *, user) -> Snapshot |
State + version + timestamps + last writer | HandleNotFound, HandleExpired |
save(handle, state, *, user, expect_version, writer=None, ttl_days=KEEP_TTL) -> Snapshot |
Versioned full replace; ttl_days renews expiry from now (None clears it) |
StaleWrite, HandleNotFound, HandleExpired, StateTooLarge |
patch(handle, ops, *, user, writer=None) -> Snapshot |
Apply commutative ops; no version needed | PatchError, HandleNotFound, HandleExpired |
touch(handle, *, user, ttl_days, writer=None) -> Snapshot |
Reset expiry from now (None = persistent) without changing state |
HandleNotFound, HandleExpired |
list(user, *, kind=None, include_expired=False) -> list[HandleInfo] |
Metadata only, most recently updated first | — |
revoke(handle, *, user) |
Delete | HandleNotFound |
sweep(user) -> int |
Physically remove expired records | — |
AsyncHandleStore exposes the same methods as coroutines (each call runs via
asyncio.to_thread); construct it with AsyncHandleStore.from_url(...) or by
wrapping an existing HandleStore.
Patch ops
| Op | Wire form (for state_patch) |
|---|---|
Append(path, value) |
{"op": "append", "path": "sources", "value": ...} |
SetKey(path, key, value) |
{"op": "set_key", "path": "profile", "key": "name", "value": ...} |
DelKey(path, key) |
{"op": "del_key", "path": "", "key": "draft"} |
Merge(mapping, path="") |
{"op": "merge", "mapping": {...}, "path": ""} |
path is a dotted path into the state ("profile.tags"); "" is the root.
Every error carries .code and .to_payload() — a structured dict written for
a model to read: stale_write includes the full current snapshot;
handle_expired is distinguished from handle_not_found.
Roadmap
Deliberately out of v1, in rough order: append-only changelog and
changes_since(handle, version); advisory activity leases; merge hooks / CRDTs
behind the same handle API; push via MCP resource subscriptions; a Postgres
backend and a non-Python sidecar.
Development
python3 -m pip install -e ".[dev]"
python3 -m pytest
python3 -m ruff check src tests
python3 -m mypy src/mcpstate
MIT licensed.
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