How to Build an AI Agent for GitHub and Notion

The workflow problem

Engineering teams maintain two parallel representations of their work: the code in GitHub and the documentation and roadmaps in Notion. These representations are supposed to tell the same story, but they diverge almost immediately. An engineer writes a new service, commits the code to GitHub, and forgets to update the architecture page in Notion. A product manager updates the roadmap database in Notion, moving a feature to “Shipped,” but the corresponding GitHub issues are still open. README files in repositories describe capabilities that were refactored months ago, while Notion pages reference APIs that no longer exist.

The divergence creates real costs. When an engineer needs to understand how a service works, they check the Notion documentation, find it is outdated, and end up reading source code directly. That reverse-engineering process takes hours for complex systems. When a product manager reviews the Notion roadmap, they see features marked as “In Progress” that were actually abandoned, and features listed as “Planned” that were already shipped under a different issue title.

Cross-team visibility suffers the most. Product, design, and leadership rely on Notion as the source of truth for what engineering is building and what has shipped. When that view is disconnected from GitHub, where the actual work happens, roadmap reviews become exercises in real-time data reconciliation rather than strategic discussions. Someone always has to pull up GitHub and manually cross-reference issues with Notion entries while everyone else waits.

Why an AI agent, not just automation

Existing GitHub-Notion integrations can mirror issues into a Notion database: each GitHub issue becomes a row, with title and status synced. This provides raw data, but raw data is not documentation. A Notion database with 300 rows of synced GitHub issues is not a roadmap; it is a data dump that no one reads.

An AI agent transforms repository data into meaningful documentation. It reads a repository’s structure, recent commits, pull requests, and README files, and generates a Notion page that describes what the service does, how it is architected, what its API looks like, and what has changed recently. This is fundamentally different from syncing fields; it requires comprehension of code context and the ability to produce human-readable narratives.

For roadmap synchronization, the agent adds the layer of interpretation that simple syncing misses. When a GitHub issue is closed, a sync tool marks the Notion row as “Done.” An AI agent reads the closing PR, understands what was actually built (which might differ from the original issue description), and updates the Notion entry’s description to reflect the actual implementation. If the implementation only partially addresses the original issue, the agent notes that and creates a follow-up entry.

The agent also handles the many-to-many relationship between code and documentation. A single Notion roadmap item like “Improve API performance” might correspond to dozens of GitHub issues across multiple repositories. The agent tracks all of them and updates the Notion entry’s status based on aggregate completion, not just individual issue status.

How it works with ACP

ACP provides your agent with access to GitHub’s repository data and Notion’s workspace, enabling it to maintain documentation and roadmaps that reflect the true state of engineering work.

GitHub tools available to the agent:

• Read repository metadata: file structure, README content, language statistics
• Access commit history and diffs for understanding recent changes
• Read pull request details: descriptions, diffs, review comments, merge status
• Query issues: titles, descriptions, labels, milestones, assignees, status
• Read release tags and changelogs
• Access GitHub Actions workflow results
• Read CODEOWNERS and contributor data
• Compare branches for release-scoped change analysis

Notion tools available to the agent:

• Create and update pages with rich content (headings, lists, code blocks, callouts)
• Create and update database entries with properties (status, date, select, multi-select)
• Read existing pages and databases for context
• Search across the workspace by text or filter
• Manage page hierarchies (nested pages)
• Update database properties and views
• Add comments and discussions to pages
• Access workspace structure (pages, databases, teams)

The agent bridges the gap between where code lives and where teams plan and document. Here is a concrete example:

Scenario 1: Automated service documentation

Trigger: The engineering manager requests updated documentation for all backend services.

Agent process for the payment-service repository:

• Reads the repository file structure: identifies an Express.js application with src/routes/, src/services/, src/models/, and src/middleware/ directories
• Reads the existing README.md (last updated 4 months ago)
• Analyzes the last 30 days of PRs: “Refactored payment processor for multi-currency” (merged), “Added webhook retry logic” (merged), “PCI compliance logging” (merged)
• Reads the src/routes/ directory to identify API endpoints

Notion output: Creates or updates a page titled “Payment Service – Architecture & API” in the Engineering Wiki. The page includes:

• Service Overview: What the service does, its tech stack, and deployment configuration
• API Reference: Endpoints extracted from route definitions, with descriptions inferred from handler logic and PR descriptions
• Recent Changes: Summary of the multi-currency refactor, webhook retry mechanism, and PCI logging additions
• Dependencies: External services and databases the service connects to, inferred from configuration files
• Stale README Warning: Notes that the repository README is 4 months old and does not reflect the multi-currency or webhook changes

Scenario 2: Roadmap synchronization

The Notion “Product Roadmap” database has an entry: “Multi-currency support” with status “In Progress.”

Agent check: The agent searches GitHub for issues and PRs related to multi-currency across all monitored repositories. It finds:

• payment-service PR “Refactored payment processor for multi-currency” – merged
• frontend issue “Multi-currency display in checkout” – open, assigned
• reporting-service issue “Currency conversion in revenue reports” – open, unassigned

Agent update: Updates the Notion roadmap entry: Status remains “In Progress.” Adds a progress note: “Backend implementation complete (payment-service PR merged June 8). Frontend checkout display in progress. Reporting conversion not started, needs assignment.” Sets a “Completion” property to 33%.

Governance and security

Source code and internal documentation both require careful access controls. ACP provides precise boundaries.

GitHub OAuth scopes: The agent uses repo scope for reading repository data, issues, PRs, and code. It does not have admin:org, admin:repo_hook, or delete_repo permissions. The agent cannot modify repository settings, manage team access, or push code. For organizations that want stricter controls, the agent can be restricted to read-only scopes (repo:status, read:org) which still allow it to read issues and PR metadata without accessing source code diffs. You select which repositories the agent can access during setup.

Notion OAuth scopes: The agent uses Notion’s API with permissions to read and write pages and databases that you share with the integration. Notion’s integration model is explicit: the agent can only access pages and databases that have been manually shared with its integration in Notion’s interface. It cannot access any content you have not explicitly granted, cannot manage workspace members, and cannot modify workspace settings.

Code sensitivity: If certain repositories contain proprietary algorithms, security-sensitive code, or infrastructure-as-code with secrets, you can exclude them from the agent’s scope. The agent will generate documentation only for repositories you designate. Even within included repositories, the agent reads code structure and PR descriptions rather than processing every line of source code, minimizing exposure.

Audit trail: Every GitHub API call and Notion page creation or update is logged with the agent’s identity, the repositories accessed, and the specific pages modified. If generated documentation contains inaccuracies, the audit trail shows which GitHub data the agent used, making it straightforward to identify the source of the error.

Example use cases

• Automated service documentation: For each repository, the agent generates a Notion page describing the service’s purpose, architecture, API endpoints, recent changes, and dependencies. These pages are refreshed weekly, so documentation stays current without manual effort.

• Roadmap status synchronization: The agent reads a Notion roadmap database and checks GitHub for the status of related issues and PRs. It updates each roadmap item’s status and adds progress notes based on actual code activity, giving product and leadership teams an accurate view of engineering progress.

• Changelog generation: When a new release is tagged in GitHub, the agent creates a Notion page summarizing the release: features added, bugs fixed, breaking changes, and contributors. This changelog is more readable than auto-generated release notes because the agent synthesizes PR descriptions into coherent narrative entries.

• Onboarding knowledge base: For each repository an engineer might work in, the agent maintains a Notion page explaining the codebase structure, key patterns, how to run the service locally, and recent architectural decisions (extracted from PRs with design discussion). New hires get a curated knowledge base instead of raw repository exploration.

• Issue-to-roadmap tracking: GitHub issues labeled with specific tags (like roadmap:q3 or feature:search) are automatically reflected in the corresponding Notion roadmap database. The agent creates entries for new issues and updates status as issues progress through the GitHub workflow.

Getting started

Connect your codebase to your documentation in minutes:

1. Sign up at cloud.agenticcontrolplane.com. Free tier includes both integrations.

2. Connect GitHub and Notion. Authorize both tools on the Data Sources page. For GitHub, select the repositories the agent should access. For Notion, share the relevant pages and databases with the ACP integration in Notion’s settings.

3. Describe your agent. Tell ACP: “For each of our backend repositories, generate a service documentation page in our Engineering Wiki in Notion. Include architecture overview, API endpoints, recent changes, and dependencies. Also sync our GitHub issues with the Product Roadmap database in Notion, updating status based on PR activity.” Your engineering knowledge base starts building itself.