Skip to main content

blopus — Python SDK

Official Python client for the Blopus web search + fetch API. Blopus is a cheap, fast web-search API backed by an owned index — built for bots and agents.

The SDK talks to exactly two data-plane endpoints: POST /v1/search and POST /v1/fetch on https://api.blopus.ai.

Topic filters

Full guide: TOPICS.md — what topic filtering does and does not do, measured. Browse the vocabulary at blopus.ai/docs/topics.

# what can I filter on?
for t in client.topics(min_docs=100000)[:10]:
    print(t.topic, t.documents)

res = client.search("data breach", topics=["cybersecurity"])
res = client.search("world cup", exclude_topics=["sports"])   # de-noise

client.topics() is free. Topics are matched exactly, so an unknown value returns zero results rather than silently widening the search — call topics() instead of guessing.

A topic describes what a publication covers, not what an individual article is about: topics=["ai"] means "pages from AI-focused sites", which is broader than "pages about AI".

Images

Ask for a hero image URL per result:

res = client.search("tesla factory", include_images=True)
for r in res.results:
    if r.image:                      # None is normal — coverage is partial
        print(r.title, r.image, f"{r.image_w}x{r.image_h}")

Off by default because it costs roughly 295 tokens per 10 results. Never promise a user a picture before you have a non-null URL in hand.

Filtering out stubs

Every result carries word_count, so you can see that a hit is a stub before reading it. min_words turns that into a filter:

res = client.search("how does raft consensus work", min_words=120)

Use it when the user wants something to READ. Leave it off for breaking news, where a two-line wire story is a legitimate answer.

Install

pip install blopus

Optional framework adapters:

pip install "blopus[langchain]"     # blopus.langchain.BlopusSearch
pip install "blopus[llamaindex]"    # blopus.llamaindex.BlopusToolSpec
pip install "blopus[crewai]"        # blopus.crewai.BlopusSearchTool

News scoping (news_only)

Set news_only=True when the question is about events — what happened, who announced what, market reaction, election results, earnings news. It searches only sources with a real newsroom, over a dedicated news channel that is faster than an unscoped search, and it drops the vendor blogs, marketing pages and documentation that otherwise crowd news results.

# events → scope it, and pair with a freshness window
client.search("what did the Fed announce", freshness="pd", news_only=True)

# documentation / reference → leave it off
client.search("kubernetes ingress example")

# wants both the announcement AND the changelog → leave it off
client.search("what's new in Python 3.14")

Omitting it searches everything, so leaving it off is always the safe choice.

Authentication

Pass an API key (blp_live_...) directly, or set BLOPUS_API_KEY:

export BLOPUS_API_KEY="blp_live_xxx"

Quickstart

from blopus import Blopus

client = Blopus()  # reads BLOPUS_API_KEY

res = client.search("who won the game last night", count=5, freshness="pd", news_only=True)
for hit in res:
    print(hit.score, hit.title, hit.url)
print("remaining quota:", res.remaining_quota)

# Fetch indexed page content
doc = client.fetch("https://example.com/article")
print(doc.title, len(doc.content))

Async

import asyncio
from blopus import AsyncBlopus

async def main():
    async with AsyncBlopus() as client:
        res = await client.search("openai news", freshness="pw")
        docs = await client.fetch([r.url for r in res])  # batch fetch
        print(docs.count, "fetched,", len(docs.failed_results), "missing")

asyncio.run(main())

search(...)

client.search(
    query,
    count=10,                 # 1..50
    freshness="all",          # pd | pw | pm | p3m | p1y | all
    news_only=False,          # True = newsroom sources only. Faster dedicated news channel;
                              # drops vendor blogs/docs. Use it for events; leave it off for
                              # documentation, tutorials, forums — or when you want both.
    include_domains=None,     # ["techcrunch.com", ...]
    exclude_domains=None,
    start_date=None,          # "YYYY-MM-DD" or epoch seconds
    end_date=None,
    language=None,            # "en", "pt", ...
    offset=0,                 # pagination, up to 200
    include_excerpt=False,    # opt in to longer excerpts
    excerpt_chars=None,       # up to 1200
)

Returns a SearchResponse (iterable over SearchResult):

res.query            # echoed query
res.results          # list[SearchResult]
res.count            # number of results returned
res.offset
res.more_results     # bool — more pages available
res.remaining_quota  # int — your remaining monthly units

# SearchResult fields:
# title, url, snippet, domain, site_name, favicon,
# published_at, age_seconds, language, score

Search always costs 1 credit, regardless of parameters or excerpt size.

fetch(url_or_urls)

# single URL -> FetchResult
doc = client.fetch("https://example.com/a")
doc.url, doc.canonical_url, doc.title, doc.content, doc.domain, doc.published_at, doc.language, doc.found

# list of URLs -> BatchFetchResponse
batch = client.fetch(["https://a.com", "https://b.com"])
batch.results          # list[FetchResult] that were found
batch.failed_results   # list[FetchFailure] (url, found=False)
batch.count            # number found (== credits billed)
batch.remaining_quota

Batches over the server cap of 50 URLs are automatically split into ≤50-URL calls, run sequentially with a small delay, and merged for you. Fetch bills per document found.

Errors

All errors subclass blopus.BlopusError:

Exception When
AuthError 401 / 403 — bad, missing or revoked key
QuotaError 402 — monthly quota exhausted
RateLimitError 429 — slow down (.retry_after)
NotFoundError 404 — no indexed content for a URL
BadRequestError 400 / 413 — malformed / too large
ServerError 5xx — gateway/backend problem
APIConnectionError network failure (no response)

Requests to 429/5xx/connection errors are retried with exponential backoff (honoring Retry-After); tune with Blopus(max_retries=...).

MCP

Blopus also exposes a hosted MCP server (search + fetch tools) at https://mcp.blopus.ai, using the same Bearer auth.

from blopus import mcp_config, print_mcp_config
print_mcp_config()        # prints the mcpServers JSON to paste into your MCP client
cfg = mcp_config()        # or get it as a dict

CLI

blopus search "who won the game" --count 5 --freshness pd --news-only
blopus search "openai" --include-domains techcrunch.com,theverge.com --json
blopus fetch https://example.com/a https://example.com/b
blopus mcp-config

License

MIT

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

blopus-0.5.1.tar.gz (29.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

blopus-0.5.1-py3-none-any.whl (30.1 kB view details)

Uploaded Python 3

File details

Details for the file blopus-0.5.1.tar.gz.

File metadata

  • Download URL: blopus-0.5.1.tar.gz
  • Upload date:
  • Size: 29.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for blopus-0.5.1.tar.gz
Algorithm Hash digest
SHA256 50d7de3f691a2c16c446cae547d80ee28de904218974cc9cfe63b4b2ab1e6639
MD5 981a760c36bcb75917a4d69f413bc187
BLAKE2b-256 2dca6c02c291345d119f047474a33687ab8edde1ff32425f129b291adff2bea9

See more details on using hashes here.

File details

Details for the file blopus-0.5.1-py3-none-any.whl.

File metadata

  • Download URL: blopus-0.5.1-py3-none-any.whl
  • Upload date:
  • Size: 30.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for blopus-0.5.1-py3-none-any.whl
Algorithm Hash digest
SHA256 a1ab1d9633a868d9cac93e9144b0939c8955a0c55543d4fa7425b529de11d451
MD5 d95021efd7fe5ec14107fe3969909004
BLAKE2b-256 aaeaea730a13983533abc66402a7cadb5c82f2ba2a1f9c7c2d892297c8ada05c

See more details on using hashes here.

Release history Release notifications | RSS feed

0.6.0

2 files

This release

0.5.1 This release

2 files

0.5.0

2 files

0.4.0

2 files

0.3.5

2 files

0.3.4

2 files

0.3.3

2 files

0.3.2

2 files

0.3.1

2 files

0.3.0

2 files

0.2.0

2 files

0.1.1

2 files

0.1.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page