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Human-friendly API testing client for terminal, desktop and web, known for readable syntax; the CLI is open source.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Test management platform unifying manual and automated test results with AI-assisted case generation, for scaling QA teams.
AI tool for engineering teams that automates code review, status updates, and answers questions about what's changing in code.
No public pricing
No public pricing
Free trial available
Free trial available
No public pricing
- ✦Human-friendly command-line HTTP client
- ✦Web and desktop GUI apps
- ✦Simple, readable request syntax
- ✦Request export/import and history
- ✦Path parameters and 'copy as command'
- ✦Open-source terminal version
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦Central test case repository with reporting dashboards
- ✦AI conversion of manual test cases into automated test scripts
- ✦CI/CD-connected automated test orchestration
- ✦Requirements-to-test traceability reporting
- ✦MCP server for connecting AI agents to test data
- ✦20+ integrations including Jira, GitHub, and Slack
- ✦AI code review
- ✦Automatic engineering status updates
- ✦Agent that answers questions and takes action
- ✦Metrics on coding time and project focus
- ✦Pushed vs landed tracking
- ✦Commit and contributor insights
- →Testing REST APIs
- →Sending and inspecting HTTP requests
- →Debugging web services
- →Sharing API requests across a team
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →QA teams consolidating scattered CI, manual, and automated results
- →Engineering orgs converting manual test backlogs into automation
- →Enterprises needing audit-ready traceability for regulated software
- →Automating code reviews
- →Keeping stakeholders updated on engineering progress
- →Understanding what's changing in a codebase
- →Tracking team productivity metrics