原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

TMCRA Agent Memory

作者:reshuibuduo版本 1.0.0-rc.1i★ –i在你的电脑上运行
注册名称io.github.reshuibuduo/tmcra-mcp-server

安装

概览

作者提供的说明(英文原文)

Role-aware Agent memory with cross-session recall, durable writes, and multi-Agent project scope.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

下载作者的 .mcpb 文件

链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。

在终端中运行这条命令

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 reshuibuduo 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7277 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7277 个服务器的 38% 更新
  • 基础检查结果等于或优于此分类中其他 7277 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

TMCRA Agent Memory 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.0.0-rc.1)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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.

中文说明

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= TMCRA_AGENT_ID=

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": " ", "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

ToolPurpose
tmcra_memory_controlInspect or explicitly change session modes, tasks and recall budgets.
tmcra_feedbackPreview exact evidence and request interactive confirmation before targeted feedback.
tmcra_recallReturn at most eight prompt-ready evidence windows for the current query.
tmcra_ingestPersist messages that already occurred, preserving role and Agent attribution.
tmcra_turn_prepareRecall before an answer and durably bind the real user turn.
tmcra_turn_commitPersist the prepared user turn and exact assistant answer as separate records.
tmcra_reconcileRetry durable pending records with the same idempotency key.
tmcra_get_jobRead one asynchronous write job state.
tmcra_wait_jobWait 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:

  1. Call tmcra_turn_prepare after receiving the current user question.
  2. Inject only the returned injectable_context as untrusted evidence.
  3. Draft the answer.
  4. Call tmcra_turn_commit with the same turn_id and the exact final answer.
  5. 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

Apache-2.0. See LICENSE and NOTICE.

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