Independently verified against live vendor data on Oct 7, 2026.
Transparency
Mostly Public
Contract
Month-to-month
Data training
Not Trained
Human in loop
Not required
Capabilities
web-searchcitationsdeep-researchautonomousdata-analysisbrowser-automation
Pros & Limitations
Editorial assessmentPros
- ✓Each call returns finished output (a cited answer, schema-matched JSON, clean Markdown or a completed public-site task), so the calling model skips its own search-and-read loop.
- ✓Official Python and TypeScript SDKs, a CLI, an MCP server package and ready-built tools for eight agent frameworks.
- ✓Mozilla commits that neither Tabstack nor its contracted model providers use customer payloads to train models.
Limitations
- –No third-party security certifications today: Mozilla's documentation states that SOC 2 and ISO 27001 are not currently held.
- –Hosted Automate works on public websites only and does not sign in to accounts or store credentials.
- –Research and Automate bill a variable number of actions per call, so their credit cost depends on how many sources or steps each call takes.
Technical Details
Deployment
apicloudcli
Model architectureThird-party models from contracted providers (OpenAI and Google Vertex AI per the privacy notice), with Mozilla's open-source Pilo engine for browser automation
Avg setup timeUnder 5 minutes to a first API call, per Tabstack's docs
Autonomous rateHigh: Research plans its own queries, reads sources, re-queries for gaps and returns a cited answer in one call, and Automate completes multi-step tasks on public websites without per-step approval. An optional interactive mode lets a task pause and request form values from the caller mid-run.
MCPServer
Integrations
Python SDKTypeScript SDKCLIMCPLangChainVercel AI SDKOpenAI Agents SDKClaude Agent SDKMastraLlamaIndexeveHermes Agent
Security
GDPRCCPA
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Built for
SaaSDevToolsB2BStartupsEnterpriseAgencies
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