OpenSERP is a free self-hosted web search for AI agents and SEO. REST API and CLI for Google, Bing, Yandex, Baidu, DuckDuckGo and Ecosia.
No API keys, no per-search billing. It loads search results in browser and returns structured JSON with source engines and ranks. Read the linked pages as clean Markdown, or connect an agent through MCP.
Works with Claude Code, Cursor, Codex, Claude Desktop and any MCP client, Open WebUI (built-in provider), n8n, and plain HTTP from any language.
API examples · CLI · Agent setup · API reference

# Start the API server
docker run --rm -p 127.0.0.1:7000:7000 karust/openserp serve -a 0.0.0.0 -p 7000
# Search Google and read the top result as Markdown
curl "http://127.0.0.1:7000/google/search?text=how+do+mcp+servers+work&extract=1"
# Docker Compose
docker compose up
# Go
go install github.com/karust/openserp@latest
openserp serve
# From source
git clone https://github.com/karust/openserp.git
cd openserp && go build -o openserp . && ./openserp serve
Prebuilt binaries for Linux, macOS and Windows are on the [releases page](https://github.com/karust/openserp/releases). Images: [`karust/openserp`](https://hub.docker.com/r/karust/openserp).
Requires Node.js 18+ and a running OpenSERP server. Add the MCP server to your client:
claude mcp add openserp -- npx -y @openserp/mcp
codex mcp add openserp -- npx -y @openserp/mcp
Cursor (~/.cursor/mcp.json), Claude Desktop, Windsurf and other clients:
{
"mcpServers": {
"openserp": { "command": "npx", "args": ["-y", "@openserp/mcp"] }
}
}
On native Windows, use cmd /c npx -y @openserp/mcp after -- in the CLI commands, or "command": "cmd", "args": ["/c", "npx", "-y", "@openserp/mcp"] in JSON.
For a remote server, add "env": { "OPENSERP_BASE_URL": "http://your-host:7000" } to the openserp JSON entry.
Tools: search, mega_search, fast_search, any_search, image_search, mega_image, extract, batch_extract, list_engines. Then just ask: "Search Google for the latest Postgres release, read the top 2 results and answer with links."
Optional for Claude Code: copy skills/openserp-search to ~/.claude/skills/ so the agent searches, reads and falls back to another engine the same way every time.
OpenSERP is a built-in web search provider. In Settings > Admin > Web Search pick openserp and set the URL (http://host.docker.internal:7000 if Open WebUI runs in Docker). See the Open WebUI guide.
A search tool for any LLM framework is a few lines with the SDK:
from openserp import OpenSERP
def web_search(query: str) -> list[dict]:
"""Search Google and return ranked results for the model."""
with OpenSERP(base_url="http://localhost:7000") as client:
res = client.search(engine="google", text=query, limit=10)
return [
{"rank": r.rank, "title": r.title, "url": r.url, "snippet": r.snippet}
for r in res.results if r.type == "organic"
]
import { OpenSERP } from "@openserp/sdk";
const client = new OpenSERP({ baseUrl: "http://localhost:7000" });
const { results } = await client.search({ engine: "google", text: "openserp", limit: 5 });
| Package | Install | Source |
|---|---|---|
@openserp/mcp - MCP server |
npx -y @openserp/mcp |
openserpapi/mcp |
@openserp/sdk - JS / TS |
npm install @openserp/sdk |
openserpapi/sdk-js |
openserp - Python |
pip install openserp |
openserpapi/sdk-python |
@openserp/n8n-nodes-openserp |
Install via n8n community nodes | openserpapi/n8n |
More in examples: agent tools, RAG context, SEO rank tracking, extraction and image search.
GET /google/search?text=how+do+mcp+servers+work&extract=1 (trimmed):
{
"query": { "text": "how do mcp servers work", "engines_requested": ["google"] },
"meta": { "took_ms": 4353, "engines_failed": [], "version": "2.1" },
"results": [
{
"rank": 1,
"type": "organic",
"engine": "google",
"title": "What Is the Model Context Protocol (MCP) and How It Works",
"url": "https://www.descope.com/learn/post/mcp",
"domain": "descope.com",
"snippet": "MCP is an open standard that lets AI applications connect to external tools, data, and services through a client-server protocol built on JSON-…",
"position": { "absolute": 1 },
"extracted": {
"format": "markdown",
"content": "The Model Context Protocol (MCP) is an open standard that defines how AI applications connect to external tools, data sources, and services. MCP clients inside AI apps send requests to MCP servers, ..."
}
},
{
"rank": 2,
"type": "organic",
"engine": "google",
"title": "No Dumb Questions: What is an MCP server and why do I ...",
"url": "https://stackoverflow.blog/2026/05/08/no-dumb-questions-mcp",
"domain": "stackoverflow.blog"
}
]
}
Results keep their source engine and rank. Ads are typed separately from organic results; extract=N attaches up to N organic pages as Markdown and records per-page failures in extracted.error. Full schema in the OpenAPI spec.
extract=N adds page Markdown under the top organic results, /extract/batch reads up to 20 URLs, and a dead link comes back as an error item instead of failing the batch.| Feature | OpenSERP | Cloud | Tavily | SerpApi | Exa |
|---|---|---|---|---|---|
| Google results | ✅ | ✅ | 🟨 Undisclosed | ✅ | ❌ |
| Search engines | 6 | 6 | Own retrieval | Many | Exa index |
| Original engine ranks | ✅ | ✅ | ❌ | ✅ | ❌ |
| Page extraction | ✅ Markdown, batch | ✅ Markdown, batch | ✅ | ✅ | ✅ |
| Self-hosting | ✅ | ❌ | ❌ | ❌ | ❌ |
| SEO monitoring, rank tracking | 🟨 | ✅ | ❌ | 🟨 | ❌ |
| PR monitoring, competitor tracking | 🟨 | ✅ Beta | 🟨 | 🟨 | ✅ API |
| AI reports and alerts | 🟨 | ✅ | 🟨 | 🟨 | 🟨 |
| Pricing | Free + infrastructure | PAYG, $0.0078/credit | $30/mo, 4k basic credits | $25/mo, 1k searches | PAYG, $4/1k Lite searches |
✅ Available · 🟨 Partial, unconfirmed or requires integration · ❌ Unavailable
Engine names: google, yandex, baidu, bing, duckduckgo (also duck, ddg), ecosia.
Use a dedicated endpoint when the source engine matters, any for ordered fallback, or balanced to compare engines. Search supports JSON, Markdown, text and NDJSON, plus language, region, date, site and file filters.
Dedicated engine endpoints:
curl "http://127.0.0.1:7000/google/search?text=golang&limit=10"
Image search:
curl "http://127.0.0.1:7000/bing/image?text=golang+logo&limit=10"
Megasearch:
curl "http://127.0.0.1:7000/mega/search?text=golang&limit=10"
/mega/search returns the same envelope as engine endpoints plus clusters: results are deduplicated by normalized URL, and clusters keep the per-engine occurrences and ranks.
| Mode | Best for | Behavior |
|---|---|---|
balanced |
Most multi-engine SERP workflows | Queries engines in parallel and merges results |
fast |
One engine selected by latency history | Uses one engine; does not fall back on failure |
any |
Ordered fallback | Tries engines in order until one succeeds, even with zero results |
# Fast mode
curl "http://127.0.0.1:7000/mega/search?text=golang&mode=fast&engines=google,bing,yandex"
# Any mode
curl "http://127.0.0.1:7000/mega/search?text=golang&mode=any&engines=google,yandex,bing"
# Balanced mode with aggregation controls
curl "http://127.0.0.1:7000/mega/search?text=golang&mode=balanced&dedupe=true&merge=true"
# Advanced filtering
curl "http://127.0.0.1:7000/mega/search?text=golang&engines=google,bing&limit=20&date=20250101..20251231&lang=EN®ion=US"
# Image megasearch
curl "http://127.0.0.1:7000/mega/image?text=golang+logo&limit=20"
List engines:
curl "http://127.0.0.1:7000/mega/engines"
URL extraction:
# Extract one URL as JSON
curl "http://127.0.0.1:7000/extract?url=https://example.com&mode=auto"
# Return clean page markdown
curl "http://127.0.0.1:7000/extract?url=https://example.com&format=markdown"
# Extract several URLs at once - returns a bare [{page_content, metadata}] array
# (Open WebUI external loader compatible); failed URLs become items with metadata.error
curl -X POST "http://127.0.0.1:7000/extract/batch" \
-H "Content-Type: application/json" \
-d '{"urls":["https://example.com","https://go.dev"],"mode":"fast"}'
# Embed extracted content under the top organic results
curl "http://127.0.0.1:7000/google/search?text=llm+observability&extract=2&format=markdown"
No server required - query an engine straight from the terminal. The CLI shares the same engines, formats, and filters as the API.
openserp search ecosia "weather in london" --format markdown

# Search results for "weather in london"
**Query:** weather in london - **Engines:** ecosia - **Took:** 866ms
## Results
### 1. London - BBC Weather
**bbc.com › weather › 2643743** - organic
Latest forecast for London ... Tonight will continue dry, and there will be mainly clear skies. Just a few patches of cloud drifting in from the north at times.
-> https://www.bbc.com/weather/2643743
### 2. London (Greater London) weather - Met Office
**weather.metoffice.gov.uk › forecast › gcpvj0v07** - organic
Remaining warm with light winds and dry. Possibly cloudy at times Monday and Tuesday, then Wednesday sunnier conditions are likely.
-> https://weather.metoffice.gov.uk/forecast/gcpvj0v07
More CLI examples:
# JSON is the default format
openserp search google "golang generics" --limit 20
# Plain text, German results
openserp search yandex "wetter berlin" --format text --lang DE --region DE
# Restrict to a site and stream NdJSON
openserp search bing "release notes" --site github.com --format ndjson
# Embed clean page content from the top 2 organic results
openserp search google "llm observability" --extract 2 --format markdown
# Browserless (raw HTTP) mode through a proxy
# (raw mode: google, yandex, baidu, ecosia)
openserp search ecosia "weather in london" --raw --proxy http://user:pass@127.0.0.1:8080
Run openserp search --help for the full flag list. Results go to stdout, logs to stderr. Set verbosity with --log_level error|warn|info|debug|trace or OPENSERP_APP_LOG_LEVEL (CLI default: warn). serve also writes ./logs.txt unless app.save_log: false.
Bing localizes by exit IP. lang sets its interface language; region sends a country hint except for US, CN and RU, which caused unrelated results in testing. For those locations, use a proxy in the target country.
OpenSERP supports HTTP and SOCKS5 proxies.
./openserp serve --proxy socks5://127.0.0.1:1080
./openserp search bing "query" --proxy http://user:pass@127.0.0.1:8080
Engines can return CAPTCHAs, rate limits or unrelated results. Browser mode does not eliminate these; try another engine or a proxy when needed.
Advanced proxy configuration is available in config.yaml. You can enable tagged proxy pools and per-request override via X-Use-Proxy: <tag> or X-Use-Proxy: direct.
Once the server is running, the interactive docs are available locally:
http://127.0.0.1:7000/docs - full schemas, error shapes, and the /health, /ready, /stats/* endpointshttp://127.0.0.1:7000/openapi.yamlTo browse the spec without running the server, see docs/openapi.yaml. For how OpenSERP works internally, see the architecture docs.
Contributions are welcome. See docs/CONTRIBUTING.md.
MIT. See LICENSE.
OpenSERP is free and open-source. Only links listed in this repository and on openserp.org are associated with the project.
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