Bandura

Overview

Bandura is a desktop workspace for API testing and local AI workflow construction. It suits developers who want visual editing backed by versionable files, local execution, and a path into CI rather than a hosted test service. Its local-first model is a strong fit for privacy-conscious individuals and teams comfortable providing their own scheduling and infrastructure.

Workflows and run history stay on the computer, and each flow is a plain-text .aether file that can be shared or committed with Git. That makes reviewable, reproducible workflow definitions practical, while the absence of hosted runs and built-in scheduling limits Bandura as a turnkey operations platform.

Key features

API workflows and imports

Bandura chains HTTP requests, passes values between steps, and asserts results, covering the core mechanics of repeatable API checks. Imports for Postman, Insomnia, OpenAPI, Bruno, HAR, and curl requests reduce the effort of moving existing collections into its workflow format. The visual canvas is useful for composing flows, while the underlying YAML-style, plain-text files remain suitable for code review and Git history.

AI providers and local models

AI features connect to Anthropic, Google Gemini, OpenAI-compatible endpoints, Groq, OpenRouter, Together, Ollama, and LM Studio. Ollama and LM Studio can run models locally without an API key or traffic leaving the machine, making them the clearest choice for sensitive development data. Bandura says it collects no telemetry, analytics, crash reports, or account data. Credentials use the operating system's secret store: Keychain on macOS, DPAPI on Windows, and Secret Service or libsecret on Linux.

CLI, CI, and assistant access

The native @bandura/cli runs the same .aether workflows in terminals and CI, with JUnit output and GitHub annotations for pipeline reporting. A local MCP server lets compatible AI assistants list, read, run, import, create, and edit flows. This combination makes Bandura more useful than a desktop-only tester for repository-based automation, although scheduled execution must be arranged through your own scheduler or CI system.

Pricing

The Free plan costs free and allows personal and commercial use with no account, paid seats, or feature tiers. There is no free trial because the plan is already free, and no quotas or usage caps are stated. It is the sensible starting point for individuals and teams evaluating local workflows without a purchasing process.

The Commercial licence costs $59, paid once, billed one-time per seat. It includes 12 months of updates, commercial use, and perpetual use of covered builds. Choose it when your organisation needs the covered commercial licence terms and per-seat purchasing; the free plan gives up that licence arrangement but does not impose paid seats or feature tiers.

Platforms

Bandura is a desktop application for Linux, macOS, and Windows, with a self-hosted deployment option. Its CLI extends those workflows into terminal and CI environments, but hosted execution is not provided.

Who it's for

Bandura is best for developers, API maintainers, and automation-minded teams that want Git-friendly workflow files, local AI options, and CI execution from one workspace. It is particularly attractive when keeping model traffic and run data on local machines matters. It is a weaker fit for organisations seeking a managed scheduler, hosted runners, or formal assurance documentation: Bandura states it has no SOC 2 report, ISO 27001 certificate, HIPAA or PCI attestation, or third-party penetration test. Support comes from the engineer who wrote the code, and the licence agreement is governed by Ukrainian law.

Pros and cons

• Pros: Plain-text .aether workflows are easy to commit, share, and review through Git.
• Pros: Broad imports and support for major remote and local AI providers ease migration and provider choice.
• Pros: Local execution, OS-backed credential storage, and no stated telemetry suit privacy-sensitive development.
• Pros: The CLI, JUnit output, GitHub annotations, and MCP server connect desktop authoring with CI and AI-assisted operations.
• Cons: There is no built-in scheduling or hosted execution, so recurring runs require your own scheduler or CI.
• Cons: The absence of listed compliance attestations and penetration testing may rule it out for regulated procurement.
• Cons: Commercial licensing is a one-time per-seat purchase after the free plan's broader no-seat terms.

Alternatives

For a focused command-line gRPC tool, choose gRPC CLI, which is free on Linux, macOS, and Windows and handles unary RPC calls from a source build. grpcui is the better match if you want a free MIT-licensed option spanning desktop, web, and self-hosted use. Choose Kreya for a freemium GUI with a free individual plan and request history limited to the latest request.

protoc-gen-doc is preferable when the goal is MIT-licensed protocol documentation rather than workflow execution. ProtoCall offers a free app with GitHub imports and manually created workspaces. Choose sabledocs for an open-source static generator requiring Python 3.11 or newer and a Protobuf descriptor file. Evans is a free open-source gRPC client. FintX suits users wanting unlimited gRPC clients, request auto-save, import/export, method tabs, a JSON editor, and projects on its $0-perpetual open-source plan. For a broader comparison, see gRPC Tools.

Verdict

Choose Bandura if you want local API and AI workflows that remain editable in Git and can run unchanged in CI. Its strongest reason to adopt is the combination of local privacy, broad imports, and a capable CLI. Look elsewhere when hosted execution, built-in scheduling, or formal compliance evidence is a purchase requirement.