- Teams building self-hosted voice agents
- Developers comparing alternatives to hosted voice AI platforms
- Operators who need telephony workflows with model-provider flexibility
BSD-2-Clause ยท Bots
Dograh
Open-source self-hosted voice AI platform with visual workflows, MCP support, BYOK model routing, and telephony.
4.3K stars 0.9K forks BSD-2-Clause license 2026-06-10 verified
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# Dograh$
pip install dograh$
npx dograh --help Open sourceSelf-hostedMCP
Overview
What is Dograh?
Dograh is an open-source voice AI platform positioned as a self-hosted alternative to hosted voice-agent products. It supports on-premise deployment, BYOK model choices, speech-to-speech or modular LLM/STT/TTS workflows, visual workflow building, MCP-native integrations, and telephony support.
Self-hosted voice platform
Dograh is positioned for on-premise and self-hosted voice AI workflows.
Voice agents often touch customer data and telephony systems, so deployment control matters.BYOK model routing
The project supports bring-your-own-key across speech-to-speech or modular LLM, STT, and TTS flows.
Voice teams can compare providers without locking the whole stack to one vendor.Visual workflows and MCP
Dograh includes a visual workflow builder and MCP-native positioning.
Voice agents need operational flows, integrations, and tool access beyond a single prompt. Use cases
What teams use it for
Ecosystem
Tags & capabilities
Comparison
How it stacks up
When to choose Dograh
Compare it with nearby bots by looking at hosting model, integration surface, license, and whether the official docs show the workflow you need.
FAQ
Questions
Is Dograh open source?
Yes. The GitHub repository is listed under the BSD-2-Clause license.
Who should evaluate Dograh?
Teams building self-hosted voice agents or comparing open alternatives to hosted voice AI platforms should evaluate it.
Decision brief
JSON
Should you use Dograh?
- Text-only chatbot projects
- Teams that do not want to operate voice, telephony, or speech infrastructure
- Verified 2026-06-10
- License: BSD-2-Clause
- Repo: dograh-hq/dograh
- Open-source signal
Deployment
self hosted, cloud
Permission surface
messages, external services
Decision signals
Self-hostable, MCP
Agent packet
Structured decision data for Dograh
This packet is the compact machine-readable view agents should use before following source links or taking action.
Capabilities
support bot, messaging, workflow, mcp
Constraints
open source, self hosted, mcp compatible
Deployment
self hosted, cloud
Permission surface
messages, external services
Recommended workflows
Connector or protocol layer
Overview
What Dograh does
What it is
It combines voice-agent workflows, telephony, BYOK model routing, visual workflow building, and MCP-native integrations.
Why it matters
Voice agents are moving into real customer workflows, where hosting, latency, provider choice, and auditability all matter.
How to evaluate it
Start with a low-risk voice workflow, test speech recognition and handoff behavior, and evaluate deployment requirements before production use.
Facts
Known metadata and operating surface
These fields are separated from editorial interpretation so agents can reason over facts and missing checks.
Resource type bot
Category Bots
Maturity active
Difficulty Unknown
License BSD-2-Clause
Pricing open source
Verified 2026-06-10
Source confidence high
Risk level moderate
Fit matrix
Where Dograh fits in an agent stack
strong
Connector or protocol layer
Dograh has multiple signals for connector or protocol layer, including matching tags, capabilities, category, or positioning.
- Connect one low-risk service, then inspect schemas, auth scope, errors, and logs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Browser automation
Dograh has at least one signal for browser automation, but should be checked against a real task before adoption.
- Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Coding agent workflow
Dograh has at least one signal for coding agent workflow, but should be checked against a real task before adoption.
- Run a small repository change and inspect the diff, tests, and rollback path.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Local or private AI stack
Dograh has at least one signal for local or private ai stack, but should be checked against a real task before adoption.
- Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Reusable skill workflow
Dograh has at least one signal for reusable skill workflow, but should be checked against a real task before adoption.
- Run one skill end to end and check whether it produces evidence or structured output.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Evaluation and observability
Dograh is not primarily positioned for evaluation and observability in the current metadata.
- Add one repeatable test case and confirm results can run again in review or CI.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs
What an agent should inspect
Likely inputs
- Repositories, files, issues, terminal output, and test results
- Tool schemas, API requests, service resources, and auth scopes
- Prompts, messages, documents, images, or model inputs
- Official setup instructions and a small real workflow
Likely outputs
- Diffs, commits, explanations, test results, or review notes
- A decision on whether this resource fits the target workflow
Evidence
Sources, claims, and missing checks
Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.
GitHub github
Repository source for code, license, issues, releases, and implementation details.
Homepage homepageOfficial or project-controlled source for this resource profile.
Dograh is listed as open source.
License metadata: BSD-2-ClauseDograh has a recorded GitHub repository: dograh-hq/dograh.
Resource facts and GitHub source link.Dograh supports these recorded deployment modes: self hosted, cloud.
OpenAgent decision signal metadata.Dograh is tagged with support bot, messaging, workflow, mcp capabilities.
OpenAgent capability taxonomy.- Dedicated docs link is missing.
- Repository freshness has not been recorded.
Next action
How to start evaluating Dograh
Inspect repository
Check license, recent activity, issues, examples, and security-sensitive code paths.
Open sourceOpen Homepage
Start from the official source before adopting third-party instructions.
Open source Compare
Alternatives and nearby resources
Use related resources to compare category fit, license, deployment model, and first-workflow behavior.
FAQ
Common questions about Dograh
Is Dograh open source?
Yes. The GitHub repository is listed under the BSD-2-Clause license.
Who should evaluate Dograh?
Teams building self-hosted voice agents or comparing open alternatives to hosted voice AI platforms should evaluate it.