# AI Toolchain Release Monitor - GitHub Release Changes (`maydit/ai-toolchain-release-monitor`) Actor Monitor GitHub releases for AI toolchains: tags, prereleases, dates, asset metadata and edited notes. Compare saved releases without downloading binaries. - **URL**: https://apify.com/maydit/ai-toolchain-release-monitor.md - **Developed by:** [Brandt May](https://apify.com/maydit) (community) - **Categories:** AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.60 / 1,000 saved observations This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## AI Toolchain Release Monitor - GitHub Release Changes AI Toolchain Release Monitor - GitHub Release Changes icon **Track release metadata and edited notes, not noisy repository popularity metrics.** Monitor GitHub releases for AI toolchains: tags, prereleases, dates, asset metadata and edited notes. Compare saved releases without downloading binaries. ### Start in under a minute 1. Paste github owner/repository into the first input field, or use the included sample. 2. Keep the five-result limit for your first run and choose **Start**. 3. Open **Observations**, **Scope and diagnostics**, or the **Readable run report** in Output. Export CSV or JSON from the dataset. ```json { "repositories": [ "ollama/ollama" ], "maxResults": 5, "itemsPerQuery": 3 } ``` No source account, API key, paid proxy or extra subscription is required for these public endpoints. Source availability and rate limits still apply. ### Who this helps AI platform teams tracking the open-source components they deploy. ### A real output sample Captured in a successful bounded Apify run; arrays and long text are shortened for readability. Values are snapshots, not live guarantees. ```json { "recordId": "ollama/ollama:416126438", "title": "v0.40.7", "repository": "ollama/ollama", "releaseId": 416126438, "tagName": "v0.40.7-rc0", "publishedAt": "2026-10-18T00:28:57Z", "prerelease": true, "assetCount": 17, "releaseNotesHash": "c5fdcfd3d1467e6d31be89897a61427b0832dadedae653475f7ed18fa202965a", "url": "https://github.com/ollama/ollama/releases/tag/v0.40.7-rc0", "observedAt": "2026-10-18T15:20:57.944Z", "comparisonStatus": "not_requested" } ``` ### What you receive One row per unique confirmed observation. Every row includes a stable `recordId`, title, source URL and observation time. | Field | Meaning | |---|---| | `repository` | Source-reported repository; missing optional values remain null. | | `releaseId` | Source-reported release id; missing optional values remain null. | | `tagName` | Source-reported tag name; missing optional values remain null. | | `publishedAt` | Source-reported published at; missing optional values remain null. | | `prerelease` | Source-reported prerelease; missing optional values remain null. | | `assetCount` | Source-reported asset count; missing optional values remain null. | | `releaseNotesHash` | Source-reported release notes hash; missing optional values remain null. | | `comparisonStatus` | not_requested, new, changed or unchanged | | `changedFields` | Fields different from your last saved observation | | `previous` | Previous saved source values when comparison is enabled | ### Saved comparisons Enable **Compare with saved observations**, choose a snapshot name, and reuse the same input scope. The first run establishes history; it cannot report changes before that point. Enable **Save only new or changed observations** for later runs if you want a change-only export. An unchanged run can correctly save zero rows. Only confirmed saved rows advance history. A bounded or failed run never establishes that a missing record was deleted. History is stored in a named key-value store in the running user's account. Use one writer per snapshot: do not overlap runs against the same snapshot. Change the snapshot name when starting a new independent workflow. ### Scope and limitations One GitHub releases page per exact public repository. Includes prereleases and excludes drafts by public API behavior. Tags without GitHub releases are outside scope. Anonymous GitHub rate limits apply. Downloads and release notes do not establish safety or compatibility. At most ten input values and five hundred saved rows per run. Each input uses a bounded source response. Shared feeds are cached within the run; public documents may require a robots.txt request. Requests are paced. Responses are capped at 8 MiB and share the run deadline. No authentication bypass or code execution is performed. HTTP 429 stops further requests. Source failures appear in SUMMARY and the HTML report, never as paid data rows. ### Pricing The configured base price is **$0.001 per saved observation**, plus **$0.00005 per start** at the default memory. Five observations cost $0.00505 at that base rate. Applicable plan discounts and the Store pricing panel govern actual charges. Set a maximum charge in Run options. Diagnostics, reports and unchanged skipped rows are not dataset result events. ### A practical workflow AI platform teams tracking the open-source components they deploy. Track release metadata and edited notes, not noisy repository popularity metrics. Start with the included five-result sample, review source links, then save your own scope as an Actor task. Use a named snapshot for repeat runs and keep source metadata with downstream exports. ### Make it recurring Save an Actor task with your inputs, then attach an Apify Schedule. For change detection, keep the same snapshot and avoid overlapping runs. Add an integration to deliver results to your own spreadsheet or workflow. No external delivery is enabled automatically. ### Frequently asked questions **Why did a repeat run return zero rows?** With change-only mode enabled, unchanged records are skipped. Check SUMMARY to distinguish this from empty matches, limits, or an upstream error. **Does a missing record mean it was deleted?** No. Searches cover a bounded source window; a record can move outside it. Missing records never become deletion claims. **Can I export or integrate the data?** Yes. Use Apify dataset exports for CSV/JSON, or the Actor API and your own integrations. No external message or delivery is enabled by default. ### Examples 1. **GitHub owner/repository: ollama/ollama** — A bounded ollama/ollama observation sample. Review source evidence and export rows or compare them in a later run. 2. **GitHub owner/repository: vllm-project/vllm** — A bounded vllm-project/vllm observation sample. Review source evidence and export rows or compare them in a later run. 3. **GitHub owner/repository: langchain-ai/langchain** — A bounded langchain-ai/langchain observation sample. Review source evidence and export rows or compare them in a later run. ### Source and support [Official source documentation](https://docs.github.com/en/rest/releases/releases). This independent Mayd IT tool is not affiliated with the source platform. Open an Actor issue with the run ID and expected result, or contact bmay@mayd-it.com. Never include credentials. ### Workflow library and related tools [Product guide](https://mayd-it.com/data-tools/actors/ai-toolchain-release-monitor/) · [Workflow and real output](https://mayd-it.com/data-tools/actors/ai-toolchain-release-monitor/workflow.md) · [All data tools](https://mayd-it.com/data-tools/) · [Use with AI](https://mayd-it.com/data-tools/ai/) # Actor input Schema ## `repositories` (type: `array`): Up to ten values. Blank uses ollama/ollama. ## `keywords` (type: `array`): Optional case-insensitive OR filter on titles within the returned source window; this is not a source-wide search. ## `maxResults` (type: `integer`): Global saved-row cap across this run. Does not promise complete source coverage. ## `itemsPerQuery` (type: `integer`): Maximum emitted records per input, from one source page or document. No pagination or complete coverage promise. ## `comparePrevious` (type: `boolean`): First comparison run establishes a baseline. Reuse the same inputs and snapshot name. One writer per snapshot. ## `onlyChanges` (type: `boolean`): Enables comparison. An unchanged run can correctly return zero rows. ## `snapshotName` (type: `string`): 1–80 letters, numbers, underscores or hyphens. Use a distinct name for independent workflows. ## `maxRunSeconds` (type: `integer`): Requests share the remaining time budget. The platform timeout may stop work earlier. ## Actor input object example ```json { "repositories": [ "ollama/ollama" ], "keywords": [], "maxResults": 5, "itemsPerQuery": 5, "comparePrevious": false, "onlyChanges": false, "snapshotName": "default", "maxRunSeconds": 60 } ``` # Actor output Schema ## `dataset` (type: `string`): No description ## `summary` (type: `string`): No description ## `report` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "repositories": [ "ollama/ollama" ] }; // Run the Actor and wait for it to finish const run = await client.actor("maydit/ai-toolchain-release-monitor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "repositories": ["ollama/ollama"] } # Run the Actor and wait for it to finish run = client.actor("maydit/ai-toolchain-release-monitor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "repositories": [ "ollama/ollama" ] }' | apify call maydit/ai-toolchain-release-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,maydit/ai-toolchain-release-monitor" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/fmRWzOZR6pLxNQFvr/builds/uJY4nMeQ0RZlJKC16/openapi.json