SpecSource is an automated bug-specification tool for Linear issues. It gathers context from Sentry, GitHub, and Slack and turns scattered signals into structured specifications, with root cause analysis and recommended fixes.
The service says it researches new Linear issues, finds related errors, code, pull requests, and Slack threads, and then compiles that information into a detailed specification. Named outputs and features include smart issue matching based on semantic similarity, automatic retrieval of code context, and cross-tool context gathering. The product also describes examples of the content it brings together, including Sentry errors and stack traces, GitHub code context and commits, and Slack team discussion. It states that the system can also query 15+ additional integrations.
SpecSource is built around issue trackers, with integrations listed for Linear, Jira, Asana, and Trello. The setup flow shown on the page involves adding Linear, Sentry, GitHub, and Slack API keys, and the service says this takes about five minutes. It is delivered as a web-based product with a free starter option and a paid Pro plan.
Pricing is presented as prepaid and usage-based. The Free plan is $0 forever and includes 50 credits, one project, all connectors, one MCP server, standard AI models, and scheduling. The Pro plan is $20 per month and includes 1,000 credits, unlimited projects, all connectors including Linear, Sentry, GitHub, Slack, and MCP, unlimited MCP servers, premium AI models, deep context gathering, and priority support. The page also says no credit card is required to get started. SpecSource.ai is identified on the site as the product name.
SpecSource is an AI project. It automates the creation of detailed bug specifications by gathering and synthesizing context from tools like Sentry, GitHub, and Slack. SpecSource is a B2B product aimed at software engineering teams. SpecSource follows a freemium model. SpecSource is available on the web.
SpecSource first shipped in 2026. Among its 5 catalogued features are AI-generated specs, linear integration, and context aggregation. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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