Context7
by upstash
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Computer or cloud★ 64,224MITUpdated today
Install
Kogcat MCP
Overview
Description from the maker (original English)
Local-first judgment layer: counter-examples & blind spots from your own knowledge base.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: stdio
- Category: Search & AI memory
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on your computer with your user’s permissions (files, network, apps).
- The registry lists no key to fill in.
You need
- PyPIPython’s uv installed (for the uvx command)
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"kogcat": {
"command": "uvx",
"args": [
"kogcat-mcp"
]
}
}
}Run this in your terminal
claude mcp add kogcat -- uvx kogcat-mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"kogcat": {
"command": "uvx",
"args": [
"kogcat-mcp"
]
}
}
}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.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"kogcat": {
"type": "stdio",
"command": "uvx",
"args": [
"kogcat-mcp"
]
}
}
}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.
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
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
- ✓ Pass
Maker matches the repo
The registry name was verified against the domain kogcat.com (the registry checks domain ownership)
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Compared with others in Search & AI memoryi
- More stars than 0% of the other 7258 servers in this category
- Published to the registry more recently than 16% of the other 7258 servers in this category
- Basic checks equal to or better than 100% of the other 7258 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Kogcat MCP safe?
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.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
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).
Is it still maintained?
The GitHub repo last changed –, and the latest version (0.46.2) reached the registry 5 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
What can I use instead?
In the same category: Context7, Codebase Memory, Exa
Alternatives
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
Codebase Memory
by DeusData
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Runs on your computer★ 48,148MITUpdated 20 days ago
Install
Exa
by exa-labs
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Runs in the cloud★ 5,213MITUpdated last month
Install
README from the maker
Open the README
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.
KogCat
AI makes the answer smoother. KogCat makes the judgment sound.
English | 中文 · Website: https://www.kogcat.com
A local-first judgment calibration layer for Claude Code and Codex. Before you act on an AI answer, it surfaces the counterexamples, the boundaries, the blind spots — drawn from a knowledge base that lives on your machine. It won't replace your model. It won't slow you down. The call stays yours.
See the difference
*"I read 30 minutes a day but nothing sticks. Should I take more detailed notes?"*
Plain AI — Try the Cornell method, highlight key passages, add Anki for spaced repetition.
KogCat — More notes will likely make it worse. The bottleneck isn't capture. It's retrieval. Your knowledge base holds a claim you marked high-confidence: *the "I get it" feeling while re-reading is the least reliable signal of real recall.* So try this once — finish a section, close the book, write what you remember. Then compare it to what you thought you had.
When it speaks up
Built for judgment, not lookup. KogCat speaks up for the calls that cost you when they're wrong — decisions, tradeoffs, comparisons, critiques, strategy. It stays quiet for the rest: lookups, definitions, code, summaries, translation. And even on a judgment call, it adds a note only when it sees something the model didn't.
- Automatic. Ask a judgment question in conversation. A note appears only when there's something worth saying — and your original answer is never touched.
- On demand.
/kogcat:queryputs your knowledge base first: a conclusion, the conditions that change it, a next step.
Install
Claude Code
/plugin marketplace add KogCat/cc-kogcat/plugin install kogcat
Codex
codex plugin marketplace add KogCat/cc-kogcatcodex plugin add kogcat@kogcat
After installing, fully quit and reopen Claude Code (or restart Codex). The first-run download only starts on the next fresh session — the install command alone won't begin it.
On first launch, KogCat quietly downloads its engine (~40 MB) and embedding model (~90 MB). Once. About a minute on a good connection. Keep working while it does — run /kogcat:status anytime to watch each piece come online.
Use it from any MCP client
KogCat's calibration engine runs as a local sidecar; the Claude Code / Codex plugin is just one client of it. Any MCP-capable tool — Cursor, Cline, Zed, VS Code, Claude Desktop — can use the same engine through a standalone stdio MCP server.
Add this to your client's MCP config (field names vary slightly by client; most use an mcpServers map):
{"mcpServers": { "kogcat": { "command": "uvx", "args": ["kogcat-mcp"] } } }
Requires uv, on macOS (Apple Silicon) or Windows x86_64 (same engine, same platforms as below). On first run it downloads the engine + embedding model and registers a background sidecar — the same one-time setup as the plugin, shared by every client on the machine. It exposes the knowledge-base tools (search, node, edges, calibrate, calibrate_review, and the memory_* family) for your model to call.
What you give up vs. the plugin. The Claude Code / Codex plugin adds two host conveniences a generic MCP client has no hook for: calibration that fires *automatically* on judgment questions, and a memory index injected into context at session start. With a standalone server your model reaches the same knowledge base, but it's the model that decides to call those tools — or you ask it to "use KogCat" — rather than a hook firing them for you. You never type the tool names (search, calibrate_review, memory_*); they're the model's to call.
Privacy
- Your knowledge base stays on your machine. KogCat reads only the folder you point it at.
- Your conversation goes to the same Claude or Codex you already use. Nothing extra, nowhere else.
- Calibration happens in a local process. The results never leave.
- The engine comes from a public release channel, checked against a sha256 manifest before it ever runs.
No account. No subscription. No one else holding your knowledge.
Commands
| Command | What it does |
|---|---|
/kogcat:query | A knowledge-base-first answer: conclusion, conditions, next step. |
/kogcat:status | A read-only local check. Reach for it if first launch seems stuck. |
/kogcat:memory-consolidate | Review and tidy saved memories — every change is yours to confirm. |
Automatic calibration needs no command.
Requirements
- Claude Code or Codex
- macOS (Apple Silicon) or Windows x86_64 — Intel Mac and Linux not yet supported
- Python 3 on
PATH— already there on macOS; on Windows, install it yourself (tick *Add python.exe to PATH*)
License
FSL-1.1-MIT — see LICENSE. Converts to MIT two years after each release.