TMCRA Agent Memory
Role-aware Agent memory with cross-session recall, durable writes, and multi-Agent project scope.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
https://github.com/reshuibuduo/tmcra-mcp-server/releases/download/v1.0.0-rc.1/tmcra-mcp-server-1.0.0-rc.1.mcpbDocumentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
TMCRA MCP Server
TMCRA MCP Server gives MCP hosts explicit access to long-term Agent memory. It recalls project evidence, writes real conversation records with speaker attribution, preserves multi-Agent project scope, and tracks asynchronous writes to a terminal state.
What it provides
- Cross-session project continuity. Recall bounded evidence from one stable project scope.
- Cross-tool collaboration. Different MCP hosts can use the same scope while keeping their own session provenance.
- Speaker and Agent attribution. User, assistant, system, and tool records remain separate; known Agent producers or targets remain attached.
- Explicit turn lifecycle. A host can prepare recall before an answer and commit the exact user/assistant turn afterward.
- Durable write recovery. Transport uncertainty enters a local SQLite queue with idempotent reconciliation.
- Verifiable receipts. Recall, ingest, and job responses are validated before the MCP host receives them.
- Nine MCP tools. Recall, ingest, prepare, commit, reconcile, get job, wait for job, session memory controls, and targeted feedback.
tmcra_memory_control exposes task selection, a 12000-character default recall budget, and normal, recall_only, off modes. Pass the exact same session_id to recall/prepare and controls. Pending older generations are discarded after a mode change; already submitted jobs remain submitted. tmcra_feedback supports ignore, correct (user-supplied replacement), and restore with a stable idempotency key. Effective feedback requires the matching backend update; check correction_index_status separately. The visual control panel is provided by the Codex and DSH distributions. This MCP package automatically discovers the shared local installation; numeric loopback HTTP is permitted only for an explicit local identity. Hosted connections require HTTPS.
Conversational corrections now require interactive host confirmation. On an actual correction request, call tmcra_memory_control(operation="correction_start") before clarification or feedback to suppress automatic capture of that discussion turn. tmcra_feedback reads exact original evidence and uses MCP form elicitation to show the source, replacement and scope; only explicit acceptance submits feedback. Rejection, cancellation, expiry or an unsupported host leaves memory unchanged. Do not substitute ingestion for a rejected correction. Host lifecycle turn IDs protect the discussion from later queue replay while preserving other identified turns. A third-party host must route elicitation to its user; the server cannot guarantee that an arbitrary client will not answer automatically. Hypothetical/quoted correction language is not authorization.
Generic MCP clients decide when to call tools. Connecting this server alone does not observe the host's before-answer or after-answer lifecycle. For automatic Codex recall and capture, install the separate TMCRA Codex Memory plugin.
Install
MCPB release
Download tmcra-mcp-server-1.0.0-rc.1.mcpb from the v1.0.0-rc.1 release and open it in an MCPB-compatible client. The bundle uses the cross-platform uv runtime. Hosted service users enter their API key in the sensitive field. For account-free Windows local memory, extract the standalone runtime, double-click Install-Local.cmd, then restart the MCP host. The local identity is discovered automatically and overrides the form's cloud URL/key; keep the API key blank for this mode. Explicit advanced TMCRA_CONFIG_FILE overrides remain authoritative. Local model acceptance limitations are documented in the runtime release.
Python wheel
python -m pip install \
https://github.com/reshuibuduo/tmcra-mcp-server/releases/download/v1.0.0-rc.1/tmcra_mcp_server-1.0.0rc1-py3-none-any.whl
Directly from GitHub with uvx
uvx --from "git+https://github.com/reshuibuduo/tmcra-mcp-server@v1.0.0-rc.1" tmcra-mcp
Authorize
Create a TMCRA account and API key, then provide it through your MCP client's secret storage or the TMCRA_API_KEY environment variable. Do not commit credentials to a repository.
TMCRA_API_KEY=<your TMCRA API key>
TMCRA_BASE_URL=https://api.tmcra.com
TMCRA_DEFAULT_SCOPE=<stable project scope, optional>
TMCRA_AGENT_ID=<known Agent identity, optional>
Users signed in through a TMCRA application can instead use its protected device file at ~/.config/tmcra/config.json. Environment variables override that file for developer and self-hosted configurations.
The server accepts only HTTPS API origins without embedded credentials, query strings, or fragments.
Register with an MCP host
After installing the wheel, an MCP host can launch:
{
"mcpServers": {
"tmcra-memory": {
"command": "tmcra-mcp",
"env": {
"TMCRA_API_KEY": "<stored securely by the host>",
"TMCRA_DEFAULT_SCOPE": "project-example"
}
}
}
}
The package also includes a Codex setup helper:
tmcra-mcp-setup install --mode explicit
tmcra-mcp-setup status --mode explicit
Tools
| Tool | Purpose |
|---|---|
tmcra_memory_control | Inspect or explicitly change session modes, tasks and recall budgets. |
tmcra_feedback | Preview exact evidence and request interactive confirmation before targeted feedback. |
tmcra_recall | Return at most eight prompt-ready evidence windows for the current query. |
tmcra_ingest | Persist messages that already occurred, preserving role and Agent attribution. |
tmcra_turn_prepare | Recall before an answer and durably bind the real user turn. |
tmcra_turn_commit | Persist the prepared user turn and exact assistant answer as separate records. |
tmcra_reconcile | Retry durable pending records with the same idempotency key. |
tmcra_get_job | Read one asynchronous write job state. |
tmcra_wait_job | Wait for a job to succeed, fail, or be cancelled. |
Every project collaborator should use the same project scope. Each conversation keeps its own session_id. Agent identity is attribution and does not split the project memory.
Recalled content is returned with trust_boundary: untrusted_memory_data. A host must treat it as evidence, never executable instructions.
Explicit lifecycle
An MCP host that wants per-turn continuity should:
- Call
tmcra_turn_prepareafter receiving the current user question. - Inject only the returned
injectable_contextas untrusted evidence. - Draft the answer.
- Call
tmcra_turn_commitwith the sameturn_idand the exact final answer. - Report pending or terminal write state accurately.
The lower-level equivalent is tmcra_recall, answer, tmcra_ingest, then tmcra_get_job or tmcra_wait_job.
Security boundary
- Credentials are read from environment or a protected TMCRA device file and are never printed by the server.
- API destinations must use HTTPS.
- Structured receipts reject malformed recall, ingest, and job responses.
- Recalled memory remains untrusted data.
- The repository contains the client-side MCP integration only. It contains no production service source code or production credentials.
- Destructive memory deletion and export are not exposed by this toolset.
See SECURITY.md for vulnerability reporting.
Development
python -m pip install -e ".[dev]"
python -m pytest -q
python -m build
python -m twine check dist/*
The tests cover receipt validation, scope and actor semantics, durable queue recovery, configuration safety, setup behavior, and a real MCP initialize/list/call smoke exchange.
License
Frequently asked questions
What is TMCRA Agent Memory?
Role-aware Agent memory with cross-session recall, durable writes, and multi-Agent project scope.
How do I install TMCRA Agent Memory?
Follow the installation steps in its documentation, shown on this page and in its repository.
Does TMCRA Agent Memory need an API key?
Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.
Is TMCRA Agent Memory open source?
Yes. Its code is on GitHub under the Apache-2.0 license.
Who maintains TMCRA Agent Memory?
It is published by reshuibuduo. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.