Clixad
Freemium
Developers who prefer terminal workflows
MandoCode
FreeOpen SourceSelf-HostedAgentic
Most CLI coding agents demand an OpenAI key, a cloud subscription, or both — and then leak your codebase through a third-party API you didn't fully audit. MandoCode skips all of that by running entirely against a local or self-hosted Ollama instance, no account required.
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Get This Tool
License: MIT Any use incl. commercial
Local-run terms: Install and run via dotnet tool; full source available under MIT; use with local Ollama models or optional cloud.
Screenshots 2
Pricing
- Model
- Free
Summary
MandoCode is a .NET CLI agent that reads your project, proposes diffs, and applies changes across files — the full plan-search-edit loop, entirely on your machine. It is built on Semantic Kernel and RazorConsole, which renders a Spectre.Console terminal UI using Razor components and a virtual DOM. The agent is designed around C# and .NET codebases, so the file understanding and diff proposals are tuned for that ecosystem. Web search is available without a key but the vendor states a free Tavily key improves reliability. The ceiling appears when you push outside .NET: community reports on the GitHub page are thin, and the tool's own framing is explicit about its target audience.
Bottom line: The right pick for a .NET team that refuses to route source code through external APIs — and the wrong pick the moment your project mixes Python services or you need a model that Ollama does not run well on your hardware.
Find your fit
Before you choose MandoCode
More options in CLI Coding Agents. Compare pricing, platforms, and features side by side.
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Pros
- Runs against local or self-hosted Ollama with no API keys required for core functionality, so your source code never leaves infrastructure you control — which means you skip the legal and security review that external AI coding tools typically trigger.
- Single `dotnet tool install` command gets the agent running, so you are not wrestling with Python virtual environments or Node version conflicts before writing a line of code.
- Project-aware planning loop — the agent reads across files, builds a plan, and proposes diffs before writing — so you review the full change set rather than discovering side effects after the fact.
- RazorConsole terminal UI renders structured, navigable output in the console without a browser or IDE dependency, which means the tool works cleanly over SSH and in headless CI environments where other agent UIs break.
- MIT-licensed and open-source, so you can audit exactly what the agent sends to the model and fork it when the default behavior does not match your workflow.
Cons
- The agent's file understanding, diff proposals, and documented use cases target .NET and C# explicitly. Teams with Python, Go, or TypeScript services in the same repository will find the agent has not been tested or tuned for those languages — at which point they are evaluating a different tool rather than configuring this one.
- Model quality and context window are entirely determined by what Ollama can run on the available hardware. On a developer laptop with a mid-range GPU, large refactoring tasks that require holding the full context of a multi-file module will start failing silently or producing partial diffs — the agent cannot compensate for a model that cannot fit the prompt.
- There is no API surface documented in the source page, which means MandoCode cannot be embedded in a larger automation pipeline or triggered by an external system. Teams that want the agent to run as a step in a CI workflow rather than interactively will need to build that wrapper themselves or switch to an agent that exposes a programmatic interface.
About
- Platforms
- .NET 8, CLI/terminal, Ollama (local or cloud)
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- June 12, 2026
Best For
Who it's for
- .NET and C# developers
- Users preferring terminal/CLI workflows
- Local Ollama-based AI coding without API keys
- Project-aware code editing and updates
What it does well
- Refactoring codebases in the terminal
- Proposing and applying code diffs
- Searching and planning across entire projects
- Running local or cloud Ollama models for coding tasks
Integrations
Compare MandoCode
Frequently Asked Questions
- Is MandoCode free?
- MandoCode offers a free option. Hosting, model usage, or optional services may have separate costs; check the pricing details and official terms.
- Is MandoCode open source?
- Yes. MandoCode is open source.
- Can I self-host MandoCode?
- Yes. MandoCode supports self-hosting on your own infrastructure.
- What platforms does MandoCode support?
- MandoCode is available on: .NET 8, CLI/terminal, Ollama (local or cloud).
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Most coding agents treat your codebase as input to a remote API call. MandoCode treats it as a local workspace: the agent reads files, builds a plan, proposes diffs, and writes changes back — all inside your terminal, against a model running in Ollama on your own hardware or a self-hosted Ollama cloud instance. The install path is a single `dotnet tool install` command. No API keys are provisioned for core functionality; an optional Tavily key unlocks more reliable web search, but the vendor documents it as optional.
The terminal interface is a distinguishing technical choice. Rather than a web dashboard or an IDE plugin, MandoCode uses RazorConsole — a library that runs Razor components with a virtual DOM and renders through Spectre.Console. The result is a structured, navigable terminal UI that goes beyond raw text scrolling without requiring a browser or Electron shell. For teams working over SSH or in locked-down CI environments, that architecture matters.
MandoCode fits .NET and C# teams who want Claude-Code-style project awareness — planning across files, proposing changes, applying diffs — without sending source to a third-party API. It fits that scenario well. It fits poorly when your stack is polyglot: the tooling, framing, and community are squarely .NET-oriented, and there is no documented evidence of comparable depth for other ecosystems. Teams running large monorepos will also hit a practical ceiling determined by the context window of whatever Ollama model they provision — the agent cannot outrun the model underneath it.
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