Integuru
Integuru is a local Python CLI/agent that reverse-engineers web platform actions from a user-captured HAR file. It generates a dependency graph of browser network requests (and cookie-based session usage) and can output runnable Python code that calls the platform’s internal endpoints to reproduce the desired action.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
The tool stores collected data locally in network_requests.har and cookies.json (sensitive session material). It uses an OpenAI API key via environment variable, but there is no explicit mention of secure secret storage, redaction, or logging controls. Security of the destination platform calls is based on user-supplied cookies rather than scoped OAuth; reverse-engineered internal endpoints and codegen increase the risk of misuse and breakage. No information is provided about TLS enforcement details, dependency vulnerability posture, or secure handling of HAR/cookie contents.
⚡ Reliability
Best When
You have permission to automate the target platform, can capture representative network traffic (HAR) and session cookies after any 2FA, and you need a one-off or short-lived integration prototype.
Avoid When
You need a stable long-term integration contract, require formal API guarantees, or cannot safely store/process cookies and HAR data; also avoid where reverse engineering may violate terms or law.
Use Cases
- • Automating a web platform action when no public API exists
- • Rapid prototyping of unofficial integrations by reusing captured browser calls
- • Reverse-engineering dependencies between network requests (IDs/parameters) to build runnable flows
Not For
- • Building compliant, officially supported API integrations
- • Platforms requiring modern challenge/attestation beyond cookies/session (e.g., robust bot defenses, device binding, or hardware-backed auth)
- • Production-grade integrations without legal/permission review and ongoing maintenance
Interface
Authentication
The tool authenticates to OpenAI using an API key. For the destination platform it relies on locally supplied browser cookies/session artifacts rather than an OAuth/API-scoped integration flow.
Pricing
No hosted pricing for this local package is described; users incur underlying LLM API usage costs.
Agent Metadata
Known Gotchas
- ⚠ Requires a correct HAR capture and valid cookies.json/session artifacts; outdated cookies will break flows.
- ⚠ If the target platform uses dynamic tokens/anti-bot measures, the generated internal calls may fail intermittently.
- ⚠ Generated code depends on reverse-engineered internal endpoints that may change without notice.
- ⚠ 2FA workflows are not automated; user must complete 2FA manually and provide resulting cookies/tokens.
Alternatives
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Scores are editorial opinions as of 2026-03-29.