Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Role-aware Agent memory with cross-session recall, durable writes, and multi-Agent project scope.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Download the maker’s .mcpb file
The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.
Run this in your terminal
Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account reshuibuduo, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.0.0-rc.1) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB on your computer.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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
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.
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 -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
uvxuvx --from "git+https://github.com/reshuibuduo/tmcra-mcp-server@v1.0.0-rc.1" tmcra-mcp
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.
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
| 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.
An MCP host that wants per-turn continuity should:
tmcra_turn_prepare after receiving the current user question.injectable_context as untrusted evidence.tmcra_turn_commit with the same turn_id and the exact final answer.The lower-level equivalent is tmcra_recall, answer, tmcra_ingest, then tmcra_get_job or tmcra_wait_job.
See SECURITY.md for vulnerability reporting.
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.
Apache-2.0. See LICENSE and NOTICE.