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Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.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)
Keyless web search and page reading for AI agents, built to get past bot walls.
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.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"searchio": {
"command": "npx",
"args": [
"-y",
"@ioserviceslabs/searchio-mcp"
]
}
}
}Run this in your terminal
claude mcp add searchio -- npx -y @ioserviceslabs/searchio-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"searchio": {
"command": "npx",
"args": [
"-y",
"@ioserviceslabs/searchio-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.
Paste into .vscode/mcp.json in your project
{
"servers": {
"searchio": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@ioserviceslabs/searchio-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.
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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 IOServicesLabs, 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 (0.1.1) reached the registry 27 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js 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.
searchio is a tool for search, page reading, and product lookup. Use it from the command line, from Python, or over HTTP. Use it as a person or as an AI agent. Search and reading need no API key.
An AI agent can set up searchio for its user in one pass. Follow these steps in order. Stop when the verify step passes.
1. Use Docker when Docker runs. Try:
docker run -i --rm ghcr.io/ioserviceslabs/searchio-mcp
The image holds the full system: fetch ladder, Rust engine sidecar, and a Chromium for the challenge tier. No other install step. Go to step 3.
2. No Docker: install from source. Needs Python 3.10 or newer.
pip install "searchio[mcp]"
curl -fsSL https://raw.githubusercontent.com/IOServicesLabs/searchio-engine/main/scripts/install.sh | sh
The pip command installs the searchio package with the MCP server from PyPI. The curl command adds the Rust engine sidecar at ~/.searchio/bin/se-serve (linux, macOS, Windows with Git Bash). The sidecar is the fast tier-2 backend. It is optional but recommended. For the latest development build use pip install "searchio[mcp] @ git+https://github.com/IOServicesLabs/searchio".
3. Add the MCP server to the client. Claude Desktop and Cursor use this config shape.
Docker:
{
"mcpServers": { "searchio": { "command": "docker", "args": ["run", "-i", "--rm", "ghcr.io/ioserviceslabs/searchio-mcp"] } } }
Source install:
{
"mcpServers": { "searchio": { "command": "searchio-mcp" } } }
4. Verify. Restart the client. Ask: "Use searchio to search the web for the current time in Tokyo." Real results mean the setup works. An error about a missing command means the config points at a path that does not exist; fix the config and retry.
Note. npx @ioserviceslabs/searchio-mcp also works as the client command in step 3. The launcher starts the Docker image when Docker runs. Without Docker it starts the local install from step 2.
You need Python 3.10 or newer.
Path A -- pip (one command):
pip install "searchio[mcp]"
searchio-mcp # MCP server on stdio, ready for an LLM client
searchio doctor checks the install. The Rust engine sidecar is optional. Install it with the curl command in the quick start, step 2.
```
Path B -- Docker (no Python needed):
docker run -i --rm ghcr.io/ioserviceslabs/searchio-mcp # stdio MCP
docker run -p 8080:8080 ghcr.io/ioserviceslabs/searchio-mcp \ searchio-mcp --transport sse --host 0.0.0.0 --port 8080
No prebuilt image for your platform? Build from source:
docker build -t searchio https://github.com/IOServicesLabs/searchio.git
The image holds the full ladder: the Python tiers, the Rust engine sidecar, and a Chromium for the challenge tier. State (clearance, sessions) persists in a volume at /root/.searchio:
docker run -i --rm -v searchio-state:/root/.searchio ghcr.io/ioserviceslabs/searchio-mcp
Path C -- from source:
git clone https://github.com/IOServicesLabs/searchio.git
cd searchio python -m venv .venv .venv\Scripts\activate # Windows
pip install -e '.[mcp]' searchio doctor
searchio doctor shows which fetch tiers work on your machine. Tier 0 is plain HTTP. Tier 1 adds TLS impersonation. Tier 2 adds a real browser for pages that block bots. Tier 2 starts on its own the first time it is needed.
Tier 2 uses the Rust [searchio-engine]( https://github.com/IOServicesLabs/searchio-engine) sidecar when a se-serve binary is present. It boots in milliseconds and has no Chromium. The Docker image includes it. On a host install, one command adds it:
curl -fsSL https://raw.githubusercontent.com/IOServicesLabs/searchio-engine/main/scripts/install.sh | sh
The installer drops the binary at ~/.searchio/bin/se-serve and searchio finds it on its own. You can also set SEARCHIO_ENGINE_BIN to any binary.
Point any MCP client at the server:
{
"mcpServers": { "searchio": { "command": "searchio-mcp" } } }
With Docker, use "command": "docker", "args": ["run", "-i", "--rm", "searchio"].
No Python at all? The npm wrapper picks a backend for you (Docker when present, else a local install):
{
"mcpServers": { "searchio": { "command": "npx", "args": ["-y", "@ioserviceslabs/searchio-mcp"] } } }
searchio search "best noise cancelling headphones 2026"
searchio search "rust async runtime comparison" --intent code searchio search "artemis mission" --domains nasa.gov searchio search "heat pump retrofit" --k 20 --json
You can set an intent: web (default), news, video, shopping, academic, code, forum, reference, local. You can also put site:nasa.gov in the query.
searchio read https://example.com/some/article
searchio read https://example.com/paper.pdf --chars 20000
The command prints the readable text. It climbs walls, bot checks, and JavaScript-only pages on its own. If a page cannot be read, you get a clear reason. You do not get an empty page.
searchio items "sony wh-1000xm5" # one row per product across retailers
searchio items "dyson v15" --domains bestbuy.com --json searchio marketplace "ford f-150" --city seattle # Facebook Marketplace, browser-backed
This part costs money. Set one key:
set ANTHROPIC_API_KEY=... # Windows
searchio research "What changed in the EU battery regulation this year, and who is affected?"
To use DeepSeek instead, set SEARCHIO_LLM_PROVIDER=deepseek and DEEPSEEK_API_KEY=.... The answer comes back with findings. Each finding cites pages the workers read.
searchio is also an MCP (Model Context Protocol) server. AI agents call it over MCP. The same tools that the CLI uses are available to the agent.
Install the MCP extra:
pip install -e '.[mcp]'
Start the server over stdio:
searchio mcp
python -m searchio.mcp
Start the server over HTTP:
searchio mcp --transport streamable-http --host 127.0.0.1 --port 8080 --path /mcp
The server has these tools:
| Tool | What it does |
|---|---|
search | Fused, ranked web search across keyless providers. |
search_items | Product listings with prices, merged across retailers. |
search_local | Facebook Marketplace classifieds near a city (browser-backed). |
youtube_transcript | Caption transcript of one YouTube video: timed segments + full text. |
read_url | Read one URL through the blocking-resistant ladder. Returns markdown. |
research | Run the multi-step research swarm on a question (needs an LLM key). |
stats | Ladder and provider health (per-domain learned tiers, block rates). |
The server also has one resource: searchio://health returns service health as a small JSON object.
The MCP server has a payment gate. It uses the x402 shape. When the gate is on, a billable tool returns a 402 (Payment Required) with an X-Payment challenge until the caller pays.
Set the gate with SEARCHIO_MCP_PAYMENT:
| Value | Result |
|---|---|
(empty, default) | Gate open. Nothing is charged. For local and dev use. |
static: | The caller must send Authorization: Bearer . Without it the tool returns a 402 + X-Payment challenge. |
This is the shape a real verifier uses. It has no ledger. When you host the server for others, put a real x402 verifier in front. The verifier checks payment, then the tool runs. This is how searchio is hosted next to SwarmIO for search and research credits.
searchio serve --port 8080
| Endpoint | What it does |
|---|---|
GET /search?q=...&intent=web&k=10&domains=a.com,b.org&freshness=week&locale=de-DE | Search results |
GET /read?url=...&session=me | Readable text of one page |
GET /items?q=...&domains=... | Product listings merged per product |
GET /marketplace?q=...&city=seattle | Facebook Marketplace listings |
GET /transcript?url=...&lang=en | YouTube caption transcript (400 not-a-video · 404 no captions · 451 refused) |
POST /research {"question": "..."} | The AI research swarm |
GET /providers, GET /stats, GET /healthz | Status |
Errors are honest status codes: 422 for a bad request, 400 for a target the policy refuses, 451 for a page blocked by an anti-bot wall, 502 or 503 when providers failed or are all cooling down after failures. A search answer lists providers_used, providers_failed and providers_skipped (breakers open, with the cooldown left).
If several people or agents share one server, give each its own session on /read. Then cookies from one never ride along on another's requests.
The Dockerfile in this repo builds the full ladder: Python tiers, the Rust engine sidecar, and a Chromium for the challenge tier. See Path B in section 1 for the build and run commands. docker compose up does the same with the state volume wired up.
Inside the container, tier 2 is the engine sidecar first; the patchright Chromium takes the pages that need a real browser (the challenge tier). Cache, learned per-domain tiers, and clearance cookies live in the searchio-state volume, so they survive restarts. Keys for the research swarm go in as environment variables, the same names as in section 10.
import asyncio
from searchio.engine import Engine
async def main(): eng = Engine() res = await eng.search("lithium iron phosphate battery lifespan", intent="web", k=5) for doc in res.docs: print(doc.title, doc.url)
doc = await eng.read("https://example.com/article") print(doc.text[:500])
items = await eng.find_items("sony wh-1000xm5") for it in items: print(it.title, it.price, it.url)
await eng.close()
asyncio.run(main())
Everything is an environment variable with the SEARCHIO_ prefix, or a line in a .env file next to where you run it. The ones people change most:
| Variable | Default | Meaning |
|---|---|---|
SEARCHIO_MAX_TIER | 2 | 0 HTTP only, 1 adds TLS impersonation, 2 adds the browser |
SEARCHIO_ROBOTS_POLICY | warn | enforce, warn, or off |
SEARCHIO_PROXY | none | Proxy URL for the HTTP tiers |
SEARCHIO_FACEBOOK_CITY | none | Default city for Marketplace searches |
SEARCHIO_CACHE_ENABLED | true | Cache fetched pages for an hour |
SEARCHIO_STATE_DIR | ~/.searchio | Where cache, profiles and clearance cookies live |
SEARCHIO_MCP_PAYMENT | | MCP payment gate (see 6.2) |
SEARCHIO_MCP_BEARER | none | Bearer token the MCP gate checks |
research calls a paid model.searchio providers lists every source and whether it is configured.searchio doctor is the first thing to run when something looks off.