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Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.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
Search
Overview
Description from the maker (original English)
Collaborative, cache-first web search for agents — cited answers from a shared live-web pool.
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 in the cloud
- Transport: Streamable HTTP
- Category: Search & AI memory
- You need to fill in: Authorization
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on the maker’s server: what you ask it goes through their server.
- You fill in yourself:
Authorization
Values marked secret are keys to your account. Never share them or paste them into a chat.
You need
- Runs in the cloudNothing to install; it connects over the internet
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
Run this in your terminal
claude mcp add --transport http search https://aimnis.com/mcp --header 'Authorization: your-value'Fill in the empty values before running it.
Or copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"search": {
"url": "https://aimnis.com/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}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": {
"search": {
"type": "http",
"url": "https://aimnis.com/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}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 address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
Your choice stays on this device in a cookie; no account needed.
Values you fill in
Authorizationsecret required HTTP headerBearer aim_YOUR_KEY — get a free eval key at https://aimnis.com/register (delivered by email).
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
We have not read this server’s tool list yet; we check endpoints in rotation.
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 with the GitHub account aimnis, which owns the repo
- … 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 checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
- … Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
- … Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint
Compared with others in Search & AI memoryi
- More stars than 0% of the other 7259 servers in this category
- Published to the registry more recently than 19% of the other 7259 servers in this category
- Basic checks equal to or better than 100% of the other 7259 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 Search 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?
You need to fill in: Authorization
Does it run on my computer or in the cloud?
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
Is it still maintained?
The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 4 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
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.
Aimnis
Collaborative Search for Agents
Search once. Answer everyone. An open-source, cache-first web-search gateway for coding agents: ask a question and get a distilled, source-cited answer instantly from a shared, always-current knowledge pool — so every search makes the pool smarter and cheaper for everyone. Like RAG, but over a communal live-web pool, not your stale private docs.
Status: public preview. The hosted service is live — get a free eval key at
[aimnis.com](https://aimnis.com) and point your agent at it in one minute
(per-agent setup). We're proving one thing in public —
that the cache hit rate compounds as the pool grows (the flywheel,
live dashboard). Follow along.
Why
Every model has a training cutoff. The moment it ships, the world moves on — new library versions, new APIs, new errors — and the model can't keep up without searching the live web on every question. That's slow, expensive, and per-vendor.
Aimnis is the shared, always-current layer in front of that: the first thing an agent checks. Ask a question; if it (or a semantically similar one) has been asked before, you get a distilled, source-cited answer instantly for near-zero cost. If it hasn't, Aimnis fetches it live, distills it, and adds it to the pool — so the next agent to ask gets it free. The corpus captures what happened *after* every model's cutoff, which no static training set can.
How it works
query└─ scrub secrets/PII (redacted before embed, search, distill, or storage) └─ local embed + normalize └─ semantic cache lookup (exact hash → vector nearest-neighbour) ├─ HIT → return the pooled, cited answer instantly (no upstream cost) └─ MISS → live search → distill into a cited answer → quality-gate → pool it
- Cache-first. The knowledge pool *is* the semantic cache (pgvector). A reworded question hits the same entry, so the pool compounds faster than exact matching would.
- Grounded, cited answers. Misses are distilled from live web results into a short answer with
[n]citations back to sources — not raw links. The answer is AI-generated (a model distills the sources) and labeled as such in the tool output, so the agent always knows it's reading a machine-written summary. - Provenance & freshness by default. Every answer carries its model, sources, and a cache timestamp (when the answer was produced or last re-distilled — not when it was last served), plus a relative age, so the agent (and our own ranking) can weigh staleness and decide when to escalate to live search.
- Cited links can be routed for a relevance signal (opt-in, aggregate-only). When enabled, a cited source link points at a signed
/r/…redirect that logs which pooled answer earned a follow-through, then forwards to the source — this is how click-through improves ranking. The source's real host is shown inline so the agent still sees where it's going, and the log records only *entry + source + host + time* — never IP, user-agent, or any user/session id. It's telemetry on the pool, not on you. It's off unless a signing secret is configured, tokens are HMAC-signed (so/rcan't be abused as an open redirector), and self-hosting points the redirect at *your own* gateway — so clicks stay on your box. - Privacy-conscious ingress. Common secret formats (API keys, tokens, private keys, connection strings) and emails are redacted *before* a query is embedded, sent to a search/LLM provider, or pooled; secret-dense queries are served live-only and never stored. This is high-precision format-based scrubbing plus an entropy pass — it catches known shapes, not every possible secret or PII, so treat it as defense-in-depth, not a guarantee. The pipeline is open source precisely so you can audit and extend it. Where it runs: self-hosted, scrubbing happens locally, so raw text never leaves your machine. Against the *hosted* gateway, the query is sent over TLS and scrubbed on ingress (in memory, before any provider call or persistence) — if you need redaction to happen before the query leaves your machine, self-host or run the local MCP server in local mode.
- Quality-gated pool. A distilled answer must pass a quality gate before it can enter the pool — a bad answer degrades to raw snippets rather than poisoning the commons.
The flywheel
The one metric that decides whether this works: cache hit rate vs. corpus size. If it climbs as the pool grows, the thesis holds. It's public from day one — trust, made measurable.
# run the live dashboard locally (see Quickstart)aimnis-dashboard # → http://127.0.0.1:8080 (hit-rate curve, corpus size, storage)
Use it with your coding agent
Aimnis speaks MCP, so any MCP-capable agent can use it as its web-search tool. The hosted endpoint means nothing to install:
- Get a free eval key at [aimnis.com/register](https://aimnis.com/register) (delivered by email; metered, revocable, terms).
- Add the remote MCP server to your agent:
URL: https://aimnis.com/mcp (MCP, streamable HTTP)Header: Authorization: Bearer aim_YOUR_KEY
Claude Code
claude mcp add --transport http aimnis https://aimnis.com/mcp \--header "Authorization: Bearer aim_YOUR_KEY"
Then, to make the model prefer Aimnis over the built-in tool, deny WebSearch in .claude/settings.json:
{ "permissions": { "deny": ["WebSearch"] } }OpenCode, OpenClaw, Hermes, Pi, REST — copy-paste snippets at aimnis.com/setup and in docs/mcp.md, plus the search / stats tool reference. Bring your own OpenRouter/search keys at registration and your cache misses run on your quota — with much higher limits.
Self-hosting instead? The same MCP server runs locally over stdio against your own pool — see Quickstart and docs/mcp.md.
Quickstart (dev)
cd serverdocker compose up -d # Postgres+pgvector (:5432)
want the keyless search path too? add SearXNG (:8888):
docker compose --profile keyless up -d
uv venv .venv && . .venv/bin/activate uv pip install -e ".[dev]" # editable install (required — see docs) python -m aimnis.migrate # apply migrations/*.sql cp .env.example .env # then fill in keys if you have them pytest # full suite against the compose DB
No OpenRouter key? Fine — Aimnis runs keyless (via SearXNG) and returns raw cited snippets, spending zero upstream quota. Add AIMNIS_OPENROUTER_API_KEY to turn on distillation. Live search is an ordered fallback chain — Brave → Tavily → Exa → SearXNG — so setting any of AIMNIS_BRAVE_API_KEY / AIMNIS_TAVILY_API_KEY / AIMNIS_EXA_API_KEY gives more reliable results, and a free tier that runs dry rolls onto the next automatically. See server/README.md for the component map.
Licensing
The code is open. The corpus is a curated compilation, licensed as such.
| Part | License |
|---|---|
Server core (server/) | AGPLv3 — network copyleft; run a modified service, share your changes |
SDKs & MCP client (clients/) | Apache-2.0 — embed anywhere, including commercial products |
| Public knowledge-pool pages | CC-BY-NC 4.0 applies to our *compilation* (curation, structure, presentation) |
On the pool's contents, honestly: pooled answers are distilled by third-party models from third-party web results. We don't claim ownership of the underlying facts or of upstream model outputs — CC-BY-NC covers our compilation, and any reuse also remains subject to the terms of the original sources and the model providers. Some provider outputs are excluded from redistribution and from any future training-data feed wherever provider terms require it, and provider-mandated attributions are carried through. A training-data feed is out of scope until the flywheel is proven (see roadmap) — this repo makes no offer to license training data.
Anti-abuse thresholds (scrubbing/dedup/quality tuning) ship with safe example defaults; production values are injected at deploy and are not part of this tree — so publishing the ruleset doesn't hand it to poisoners.
Status & roadmap
Gated roadmap, Gate 0 → Gate 4. Gate 0 complete (ToS audit, niche, naming, licensing locked). Gate 1 in progress — gateway + semantic cache + public flywheel dashboard are built and dogfooded; the pass/kill test is the hit-rate curve bending upward. Ads, billing, community compute, and the training-data feed are explicitly out of scope until the flywheel is proven.