Install
$ agentstack add mcp-kosminus-reasonflow ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ● Environment & secrets Used
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
ReasonFlow
SDK-first, MCP-native agent orchestration framework.
from reasonflow import DAG, LLMNode, CodeNode, DecisionNode, parallel
@CodeNode
def step1(state):
return {"greeting": f"Hello, {state['name']}!"}
@CodeNode
def step2(state):
return {"upper": state["greeting"].upper()}
dag = DAG("hello")
dag.connect(step1 >> step2)
result = dag.run(name="World")
print(result["upper"]) # HELLO, WORLD!
Install
pip install reasonflow
Setup
Copy .env.example to .env and add your API keys:
cp .env.example .env
Supports cloud providers (OpenAI, Anthropic, Google) and local models via Ollama — use model names like ollama/llama3 in @LLMNode(model=...).
Features
- 4 node types:
LLMNode,MCPNode,CodeNode,DecisionNode >>operator for DAG constructionparallel()for concurrent branches- Automatic cost/token tracking per node
- Built-in retries with error-type awareness
- MCP-native tool integration
- JSON execution traces
- CLI:
reasonflow run,reasonflow trace - Debug mode:
--debugflag,DAG(debug=True), or per-node.debug()
Examples
# Research pipeline — parallel branches + LLM synthesis
reasonflow run examples/research_pipeline.py -v topic="AI safety"
# Multi-model debate — 3 LLMs argue in parallel, judge synthesizes
reasonflow run examples/multi_model_debate.py -v question="Should we adopt microservices?"
# Email drafter — bullets → LLM draft → LLM review → save
reasonflow run examples/email_drafter.py -v recipient="Engineering" -v subject="Q1 Update"
# Code reviewer — git diff → LLM code review → saved report
reasonflow run examples/code_reviewer.py -v repo_path="."
# CSV analyzer — parse CSV + compute stats → LLM insights
reasonflow run examples/csv_analyzer.py -v csv_path="data.csv"
# Git changelog — git log → LLM-generated release notes
reasonflow run examples/git_changelog.py -v repo_path="."
# Web scraper — fetch URL → strip HTML → LLM summary
reasonflow run examples/web_scraper_summarizer.py -v url="https://example.com"
# Log analyzer — read logs → grep errors → LLM categorize
reasonflow run examples/log_analyzer.py -v log_path="/var/log/system.log"
# Health check — parallel system checks → DecisionNode → alert/report
reasonflow run examples/health_check.py
# Test runner — pytest → DecisionNode → LLM failure analysis
reasonflow run examples/test_runner.py -v test_path="tests/"
# Process manager — ps/grep/kill via CodeNodes
reasonflow run examples/process_manager.py
# Run & analyze — execute a Python script → LLM analyzes output
reasonflow run examples/run_and_analyze.py
# Docker cleanup — parallel inventory → decide → prune (dry-run default)
reasonflow run examples/docker_cleanup.py
# Debug mode — see each node's output
reasonflow run examples/process_manager.py --debug
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: kosminus
- Source: kosminus/reasonflow
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.