Pricing
$3.00 / 1,000 results
GitHub Repository Search β Repos to JSON
Search GitHub repositories by keyword. Stars, language, last push, open issues, forks as JSON for developer-tooling & research AI agents. $3 per 1,000, no coding.
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$3.00 / 1,000 results
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Search GitHub repositories by keyword or qualifier and get stars, language, activity, issues and URL as JSON β $0.003 per repo.
Whether you are vetting a dependency, tracking a competitorβs open-source, or finding tools for a build, the signal is in the repo metadata: stars, recency, issue load. This actor turns a GitHub search into structured repo records so developer and research agents can rank and vet repositories without parsing HTML.
What this actor does
- Search GitHub repositories with full query-qualifier support (language:, stars:, topic:, β¦)
- Each result: full name, description, stars, language, forks, open issues, last-push + created dates, URL
- Filter by keyword/postedAfter; sorted by stars by default
- Batch many queries per run; cap spend with maxResults
- Unauthenticated (no token/setup) β best for targeted searches; large batches may hit GitHub's public rate limit
You only pay for successful results β failed or empty lookups cost nothing.
Why pick this Actor
- Flat repo records with stars, forks, open issues, language, and last-push date β ranking-pipeline-ready without parsing GitHub's nested API shapes
- Per-result pricing ($0.003/result) with a hard
maxResultsspend cap β empty lookups cost $0 - Flat, stable JSON schema with
sourceUrl+scrapedAton every item β citation-ready for RAG and grounding - Batch many queries in one run; overlapping results are deduplicated and charged once
- MCP server, OpenAPI schema, and LangChain/CrewAI tool support out of the box β no glue code
Sample output
Each dataset item is flat, typed JSON with a sourceUrl and scrapedAt for citation/grounding:
{"query":"ai agent","source":"github","title":"NousResearch/hermes-agent","stars":190459,"language":"Python","pushedAt":"2026-06-11T09:30:15.000Z","url":"https://github.com/NousResearch/hermes-agent","sourceUrl":"https://api.github.com/search/repositories?q=ai+agent","scrapedAt":"2026-06-11T09:00:00.000Z"}
Input
{"queries":["ai agent"]}
| Field | Type | Description |
|---|---|---|
queries / query | array / string | GitHub search query. One or many. |
maxResults | integer | Hard spend cap (billed per result). |
keywords / postedAfter | filters | Narrow results; enable delta/scheduled runs. |
How much does it cost
Pay-per-result: $0.003 per successful result. No subscription, no compute-unit guesswork, no charge for empty results. An orchestrator can cap spend with maxResults.
How to use it with AI agents (MCP), Claude, and the API
Claude Desktop / Claude Code via Apify MCP
{"mcpServers":{"apify":{"command":"npx","args":["-y","@apify/actors-mcp-server","--actors","oblanceolate_mandola/github-repo-search"],"env":{"APIFY_TOKEN":"<YOUR_APIFY_TOKEN>"}}}}
Python (Apify API)
from apify_client import ApifyClientclient = ApifyClient("<YOUR_APIFY_TOKEN>")run = client.actor("oblanceolate_mandola/github-repo-search").call(run_input={"queries":["ai agent"]})for item in client.dataset(run["defaultDatasetId"]).iterate_items():print(item)
TypeScript (Apify API)
import{ ApifyClient }from'apify-client';const client =newApifyClient({ token:'<YOUR_APIFY_TOKEN>'});const run =await client.actor('oblanceolate_mandola/github-repo-search').call({"queries":["ai agent"]});const{ items }=await client.dataset(run.defaultDatasetId).listItems();console.log(items);
LangChain / CrewAI tool
from langchain_apify import ApifyActorsTooltool = ApifyActorsTool("oblanceolate_mandola/github-repo-search")# agent calls it autonomously
OpenAPI schema for self-integrating GPT agents is auto-exposed at the Actor's API tab.
Data & compliance
Reads only publicly accessible endpoints. No login, no credential harvesting, no CAPTCHA bypass. Every result carries its sourceUrl so downstream agents can cite and re-verify.
FAQ
Do I need a GitHub account or token?
No β this actor uses GitHub's public unauthenticated search, so there is no setup. Public search is rate-limited (~10 requests/min), which is plenty for targeted queries; for very large batches, run them in smaller scheduled chunks.
Can I use search qualifiers?
Yes β anything GitHub search supports, e.g. "language:go stars:>500 pushed:>2026-01-01".
How are results ordered?
By stars, descending, so the most prominent repositories come first.
Can AI agents call this Actor directly?
Yes β via the Apify MCP server (snippet above), the OpenAPI schema on the Actor's API tab, or the LangChain/CrewAI tool wrapper. Results are flat JSON with sourceUrl and scrapedAt on every item, so downstream agents can cite and re-verify.
What happens when there are no results?
You pay nothing. Billing is per dataset item delivered, so an empty lookup costs $0, and the run log states why (no match, source rate limit) instead of failing silently.
Changelog
- 1.0 β Initial release: github.
