GitHub Issues & Pull Requests Scraper

Extract public GitHub issues and pull requests from repositories or GitHub search queries.

Use this actor to monitor open-source demand, support pain, competitor roadmaps, bug reports, feature requests, and pull request activity.

What does GitHub Issues & Pull Requests Scraper do?

This actor turns public GitHub issue and pull request search results into a clean dataset.

It accepts repository names such as microsoft/vscode.

It also accepts GitHub issue search queries such as repo:microsoft/vscode is:issue label:bug.

The output includes issue and pull request metadata, labels, author details, timestamps, comments, reactions, and source-query provenance.

Who is it for?

DevRel teams

Track what developers ask for across important open-source projects.

Product managers

Find repeated bugs, integration gaps, feature requests, and migration pain.

Support teams

Monitor public issues mentioning your product, API, SDK, or competitor.

Founders and growth teams

Discover high-intent leads from public problems and requests.

AI and data teams

Collect structured issue and pull request records for RAG, classification, or trend analysis.

Why use this actor?

GitHub search is powerful, but manual monitoring is slow.

This actor saves repeatable searches as exportable data.

You can schedule it, connect it to integrations, or call it from code.

You get consistent fields instead of copying records by hand.

What data can you extract?

Input overview

You can use repositories, search queries, or both. If both lists are omitted, the Actor runs the documented microsoft/vscode example with the normal maxItems limit.

If you provide both, the actor processes all sources in one run until maxItems is reached.

Repositories

Use repository names in owner/name format.

Examples:

• microsoft/vscode
• nodejs/node
• facebook/react

Repository URLs are also accepted.

Search queries

Use GitHub issue search syntax.

Examples:

• repo:microsoft/vscode is:issue label:bug
• kubernetes error "good first issue"
• org:vercel is:pr state:open

Example input

{
  "repositories": ["microsoft/vscode"],
  "searchQueries": [],
  "state": "open",
  "includeIssues": true,
  "includePullRequests": true,
  "labels": [],
  "maxItems": 25
}

Input settings

Search filters

State

Choose open, closed, or all.

Include issues

Enable this to save GitHub issues.

Include pull requests

Enable this to save GitHub pull requests.

Labels

Add label names such as bug, documentation, or good first issue.

The actor appends these filters to generated repository searches.

Updated since

Use since to collect records updated after a date.

This is useful for scheduled monitoring.

Output example

{
  "repository": "microsoft/vscode",
  "type": "issue",
  "number": 123,
  "title": "Example issue title",
  "state": "open",
  "url": "https://github.com/microsoft/vscode/issues/123",
  "authorLogin": "octocat",
  "labels": ["bug"],
  "commentsCount": 4,
  "createdAt": "2026-01-01T00:00:00Z",
  "updatedAt": "2026-01-02T00:00:00Z"
}

How to scrape a repository

1. Open the actor input form.
2. Add one or more repositories.
3. Choose state and issue / pull request options.
4. Set maxItems.
5. Run the actor.
6. Export the dataset as JSON, CSV, Excel, or via API.

How to monitor a keyword

1. Add a GitHub search query.
2. Include words, labels, organizations, or repositories.
3. Set since for incremental monitoring.
4. Schedule the actor daily or weekly.
5. Send new rows to your destination system.

Tips for better results

💡 Use repository-specific queries for precise output.

💡 Use labels to focus on bugs, feature requests, or onboarding tasks.

💡 Use since for recurring jobs so each run stays small.

💡 Start with maxItems: 25 before scaling up.

💡 Add a GitHub token only when you need higher rate limits.

Rate limits

Public GitHub data can be fetched without a token for small runs.

GitHub applies rate limits to unauthenticated API usage.

For larger monitoring workflows, provide a GitHub token in the optional secret input.

The token is used only to request public API data with a higher rate limit.

GitHub search returns at most 1,000 matches for each query. maxItems remains a total cap across all sources, so larger values are useful only when you provide multiple repositories or search queries. Each run stores a RUN_SUMMARY key-value record that identifies incomplete search results and sources that may have reached the per-query cap.

Invalid GitHub search queries and conflicting state filters fail clearly instead of returning a successful empty dataset. If GitHub rate limits a request, the actor retries a bounded number of times and then fails with guidance to wait or provide githubToken.

GitHub search returns at most 1,000 matches for each query. maxItems remains a total cap across all sources, so larger values are useful only when you provide multiple repositories or search queries. Each run stores a RUN_SUMMARY key-value record that identifies incomplete search results and sources that may have reached the per-query cap.

Invalid GitHub search queries and conflicting state filters fail clearly instead of returning a successful empty dataset. If GitHub rate limits a request, the actor retries a bounded number of times and then fails with guidance to wait or provide githubToken.

Integrations

Send dataset rows to Google Sheets for manual review.

Send issue records to Slack or Discord for support triage.

Load pull request data into a warehouse for engineering analytics.

Use webhooks to trigger workflows when new matching issues appear.

Feed output into LLM classification or RAG pipelines.

API usage

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/github-issues-pull-requests-scraper').call({
  repositories: ['microsoft/vscode'],
  state: 'open',
  maxItems: 25
});
console.log(run.defaultDatasetId);

Python

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/github-issues-pull-requests-scraper').call(run_input={
    'repositories': ['microsoft/vscode'],
    'state': 'open',
    'maxItems': 25,
})
print(run['defaultDatasetId'])

cURL

curl -X POST "https://api.apify.com/v2/acts/fetch_cat~github-issues-pull-requests-scraper/runs?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"repositories":["microsoft/vscode"],"state":"open","maxItems":25}'

MCP usage

You can run this actor from Apify MCP tools.

Use this tool URL pattern:

https://mcp.apify.com/?tools=fetch_cat/github-issues-pull-requests-scraper

Add it to Claude Code with:

claude mcp add apify-github-issues "https://mcp.apify.com/?tools=fetch_cat/github-issues-pull-requests-scraper"

For a JSON MCP configuration, use:

{
  "mcpServers": {
    "apify-github-issues": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.apify.com/?tools=fetch_cat/github-issues-pull-requests-scraper"
      ]
    }
  }
}

Example MCP prompts

Use these prompts after connecting the actor through MCP.

Example prompt ideas:

Claude Code prompt

"Use the Apify GitHub Issues & Pull Requests Scraper tool for microsoft/vscode and summarize the top open bugs."

Claude Desktop prompt

"Use the MCP GitHub issues scraper to find recent open pull requests in nodejs/node and group them by likely topic."

Agent workflow prompt

"With the Apify MCP tool, monitor GitHub issues mentioning our SDK every day and send high-priority records to Slack."

Common workflows

Competitive intelligence

Track public issues in competitor repositories.

Look for bug patterns, integration gaps, and roadmap signals.

DevRel monitoring

Find developers asking for help with your ecosystem.

Prioritize responses by comments, labels, or recency.

Product discovery

Collect feature requests and pain points from open-source communities.

Classify titles and body excerpts with your preferred AI model.

Engineering analytics

Export pull request metadata for reporting on activity and review flow.

Combine with other GitHub or CI data sources.

Troubleshooting

The run says GitHub rate limit reached

Use a smaller maxItems, wait for the reset window, or provide a GitHub token.

My query returns no data

Check the query in GitHub search first, then copy the same syntax into searchQueries.

I only want issues, not pull requests

Set includeIssues to true and includePullRequests to false.

I only want pull requests

Set includeIssues to false and includePullRequests to true.

Data quality notes

The actor returns public GitHub metadata available through GitHub search.

Some fields may be empty when GitHub does not provide that value.

Body text is saved as an excerpt to keep rows compact.

Use url to open the full public issue or pull request.

Legality and responsible use

This actor extracts public GitHub issue and pull request data.

You are responsible for using the data in accordance with GitHub's terms, privacy expectations, and applicable laws.

Do not use the output for spam, harassment, or abusive automation.

Respect users and project maintainers.

Support

Report a bug from the Actor page when a run fails or the output looks wrong. Include:

• Run ID or run URL
• Input JSON
• Expected output
• Actual output
• One reproducible public URL or repository/search query

Privacy and data handling

This Actor only requests the permissions needed to run the input you provide. It uses your input (such as URLs, search terms, identifiers, filters, and limits) only to fetch the requested public data from the relevant source site or API for this Actor, then writes results to your Apify dataset/key-value store.

Data may pass through Apify platform services and Apify Proxy during the run, and requests are sent only to the target site or public data provider required for this Actor's results. FetchCat does not send your inputs or outputs to advertising networks, data brokers, or model-training services, and does not retain run data outside Apify storage after the run except when you explicitly share run details for transient support debugging.

You are responsible for using this Actor lawfully, respecting the target site's terms, and avoiding unnecessary personal or sensitive data in inputs. Review the output before storing, sharing, or combining it with other data.