Kendr
Health Pass
- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 13 GitHub stars
Code Pass
- Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Pass
- Permissions — No dangerous permissions requested
This tool is an open-source multi-agent orchestration platform designed for research, project management, and software automation. It allows users to run long-running AI tasks via a web interface or terminal on their own infrastructure.
Security Assessment
Overall Risk: Medium. The platform is designed to orchestrate AI agents and automate workflows, meaning it inherently has the capability to execute shell commands and make external network requests, particularly to LLM providers like OpenAI, Anthropic, or Google. It requires you to supply your own API keys for these external AI services. The automated code scan (12 files) did not find any hardcoded secrets or dangerous patterns, and the tool requests no inherently dangerous permissions. However, because it acts as an orchestration layer that runs locally and processes your data through external APIs, standard caution is advised.
Quality Assessment
The project is actively maintained, with its most recent push occurring today. It uses the highly permissive MIT license and has clear, structured documentation. With 13 GitHub stars, the community trust level is currently very early-stage. It is a relatively new and small project, meaning it has not yet been extensively battle-tested by a wide audience.
Verdict
Use with caution: the codebase is active, clean, and transparent, but its early-stage maturity and requirement to handle external API keys require you to ensure your local infrastructure and environment variables are secured.
Kendr is multi-agent orchestration which user can run in their own controlled infrastructure. Designed for long running tasks.
Kendr
Open-source multi-agent intelligence platform — Web UI + CLI for research, project management, and software automation.
Kendr is a Python runtime that combines specialized AI agents, a web-based chat and project UI, multi-source research, durable memory, and structured run artifacts. Use it from the browser or the terminal.
Quickstart · CLI Reference · Configuration · Integrations · Examples
Install
Requirements
- Python 3.10 or newer — python.org/downloads
- Git — git-scm.com
- An OpenAI API key (or Anthropic / Google / local Ollama — see LLM Providers below)
macOS / Linux — one command
git clone https://github.com/kendr-ai/kendr.git
cd kendr
./scripts/install.sh
After it finishes, reload your shell and run kendr --help to confirm the install:
source ~/.zshrc # zsh (macOS default)
# or
source ~/.bashrc # bash (Linux default)
kendr --help
Windows — PowerShell
Open PowerShell (not CMD) and run:
git clone https://github.com/kendr-ai/kendr.git
cd kendr
powershell -ExecutionPolicy Bypass -File .\scripts\install.ps1
Open a new terminal after the script finishes, then verify:
kendr --help
Manual install (any platform)
If you prefer to control the environment yourself:
git clone https://github.com/kendr-ai/kendr.git
cd kendr
# Create and activate a virtual environment
python3 -m venv .venv
source .venv/bin/activate # macOS/Linux
# .venv\Scripts\activate # Windows PowerShell
# Install kendr
pip install -e .
# Verify
kendr --help
Install with pip (no git clone)
If you just want the package without cloning the repo:
pip install kendr-runtime
kendr --help
Note: Running
kendr uifrom a pip install requires the repo to be present for the HTML assets. Clone + install is recommended for the full experience.
LLM Providers
Kendr ships with OpenAI by default. Install optional packages to add more providers:
| Provider | Install command | Models |
|---|---|---|
| OpenAI (default) | included | GPT-4o, GPT-4o-mini, o1, o3 |
| Anthropic Claude | pip install 'kendr-runtime[anthropic]' |
claude-3-5-sonnet, claude-opus |
| Google Gemini | pip install 'kendr-runtime[google]' |
gemini-2.0-flash, gemini-1.5-pro |
| Local Ollama | pip install 'kendr-runtime[ollama]' |
llama3, mistral, phi3, … |
| All of the above | pip install 'kendr-runtime[full]' |
everything |
Or use the install script with --full:
./scripts/install.sh --full # macOS/Linux
.\scripts\install.ps1 -Full # Windows
First-Time Setup
After installing, set two required values:
# Your LLM API key
kendr setup set openai OPENAI_API_KEY sk-...
# Where kendr writes output files
kendr setup set core_runtime KENDR_WORKING_DIR ~/kendr-work
# Check everything is configured
kendr setup status
Or copy .env.example to .env and fill in the values manually.
Launch the Web UI
kendr ui
# or the shorter alias:
kendr web
Opens the web interface at http://localhost:5000 with:
- Chat — multi-agent chat with streaming output and plan cards
- Projects — open any local code project, chat with an AI that understands your codebase, manage files, run terminal commands, view git status
- Setup & Config — configure API keys and LLM providers in the browser
- Run History — browse every past run and its output artifacts
- LLM Models — view and switch between available models
CLI Quick Reference
# Research
kendr run "Analyse the AI chip market: key players, supply chain, investment outlook."
kendr research --sources arxiv,web --pages 15 "Advances in LLM reasoning 2024"
# Software project generation
kendr generate --stack fastapi_postgres "Task management API with auth and tests."
kendr generate --stack nextjs_prisma_postgres "Blog platform with markdown and auth."
# SuperRAG knowledge sessions
kendr run --superrag-mode build --superrag-new-session --superrag-session-title "docs" \
--superrag-path ./docs "Index my documentation."
kendr run --superrag-mode chat --superrag-session docs "What are the install requirements?"
# Shell command execution (with approval gate)
kendr run --os-command "df -h" --os-shell bash --privileged-approved "Check disk usage."
# Gateway (required for communication integrations and REST API)
kendr gateway start
kendr gateway status
kendr gateway stop
What You Can Do
| # | Capability | Entry point | Status |
|---|---|---|---|
| 1 | Web UI — chat, projects, config, history | kendr ui |
Stable |
| 2 | Deep research + document generation | kendr run / kendr research |
Stable |
| 3 | Multi-agent project generation | kendr generate |
Beta |
| 4 | SuperRAG knowledge engine | kendr run --superrag-mode |
Stable |
| 5 | Local command execution | kendr run --os-command |
Beta |
| 6 | Unified communication suite | kendr run --communication-authorized |
Beta |
Feature Status Matrix
| Status | Areas |
|---|---|
| Stable | Web UI, core CLI, setup-aware routing, SuperRAG sessions, research synthesis, local-drive intelligence |
| Beta | Project generation, long-document pipeline, gateway HTTP surface, communication suite, AWS workflows |
| Experimental | Dynamic agent factory, generated agents, voice/audio workflows |
Capability Highlights
Web UI and Project Workspace
kendr ui
# → http://localhost:5000
The web interface gives you a full project workspace:
- Open any local Git repository and chat with the AI about your code
- Auto-generates a
kendr.mdproject context file if one doesn't exist - Model selector and live context-window usage bar in the chat input
- File browser, integrated terminal, and git status panel
- Recent chat history per project
Deep Research and Document Generation
Multi-source research that synthesises web, academic, patent, and local evidence into structured reports.
kendr run --current-folder \
"Create an intelligence brief on Stripe: business model, competitors, strategy, risks."
kendr run --long-document --long-document-pages 50 \
"Produce an exhaustive global gold market investment report."
Multi-Agent Software Project Generation
Blueprint → scaffold → build → test → verify → zip export, fully automated.
kendr generate --stack fastapi_react_postgres \
"SaaS starter with billing, admin dashboard, and CI/CD."
Available stacks: fastapi_postgres, fastapi_react_postgres, nextjs_prisma_postgres, express_prisma_postgres, mern_microservices_mongodb, pern_postgres, nextjs_static_site, django_react_postgres, custom_freeform.
SuperRAG Knowledge Engine
Zero-config vector search over local files, URLs, databases, and OneDrive content.
kendr run --superrag-mode build --superrag-new-session \
--superrag-session-title "product_docs" --superrag-path ./docs \
"Index our documentation."
kendr run --superrag-mode chat --superrag-session product_docs \
--superrag-chat "What are the installation requirements?"
Docs
- Quickstart — install, configure, first run
- CLI Reference — every subcommand and flag
- Configuration — every environment variable
- Integrations — vector backends, communication providers, security tools
- Agents — workflow families and the full agent inventory
- Architecture — runtime flow, discovery, persistence
- Security — safety boundaries and privileged controls
- Examples — copy-paste CLI examples for every workflow
- Troubleshooting — common first-run issues
Contribute
Contribution baseline:
- keep changes grounded in real code and verified workflows
- preserve setup-aware gating and runtime behaviour unless fixing a bug
- update tests and docs with user-facing changes
- run
python scripts/verify.pybefore opening a PR
Community
- Join the Kendr Discord community for live chat, collaboration, Q&A, and announcements: https://discord.gg/GgU8UEdn
- Track ongoing work, open issues/feedback, and CI results on the GitHub project view
- The badges above pull live GitHub metrics (stars, forks, watchers, issues, workflows + more) so you can see how the project is performing in real time.
Contributors
Names and avatars shown above are generated automatically from GitHub contributions, so the list reflects the latest community participation without manual updates.
Under the Hood
- multi-agent orchestration runtime in
kendr/runtime.py - web UI server (chat + project workspace) in
kendr/ui_server.py - CLI entrypoint in
kendr/cli.py - dynamic agent registry and discovery in
kendr/discovery.py - multi-provider LLM routing in
kendr/llm_router.py - project context management in
kendr/project_context.py - rich terminal output in
kendr/cli_output.py - setup and integration catalog in
kendr/setup/ - durable SQLite persistence in
kendr/persistence/ - multi-source research infrastructure in
tasks/research_infra.py - optional HTTP gateway in
kendr/gateway_server.py - MCP server endpoints in
mcp_servers/
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