AI Agents That Work With LangGraph (2026)
As of Sep 15, 2026, 11 AI agents in the KanonAgent index are judged to connect to Langgraph; this page covers the top 10 by real traction (10 with the source line quoted). Judgements come from quoted evidence, not vendor claims — where we cannot read it, we leave it blank.
Connecting agents to LangGraph unlocks streaming, persistence, checkpointing, and structured multi-step execution on your own infra. This matters now because teams are moving from prototypes to production deployments that require tracing, control loops, and self-hosted runners. The agents below show concrete jobs that become reliable once wired into LangGraph.
Updated 2026-09-15 · 10 products · live data from KanonAgent
1. Multi-Agent-CAD948 upvotes
Multi-Agent-CAD turns natural-language descriptions into engineering-compliant CAD drawings for prototypes; LangGraph supplies the constrained test-time compute loop that powers build123d.
source: “Powered by build123d”
2. deepagents65 upvotes
deepagents gives developers a batteries-included harness for autonomous tool-calling agents; the integration supplies LangGraph streaming, persistence, and first-class tracing out of the box.
source: “built on LangGraph (streaming, persistence, checkpointing) with first-class tracing, evaluation, and deployment via LangSmith”
LoopGain stops runaway agent loops with control theory instead of crude max_iterations; it ships pre-built adapters so the same logic runs inside LangGraph workflows.
source: “Pre-built adapters for [LangGraph](#langgraph), [CrewAI](#crewai), [AutoGen](#autogen-v04), [LangChain](#langchain), [OpenAI Agents SDK](#openai-agent”
Local Search Agent replaces embedding-based RAG with BM25 keyword search over private data; LangGraph runs the agent loop that orchestrates Meilisearch calls.
source: “BM25 keyword search via Meilisearch, structured metadata, and a LangGraph agent loop”
Charter lets enterprises run production agents on their own infrastructure for data control; LangGraph model and tool calls export as OpenTelemetry traces consumable by Jaeger or Datadog.
source: “Model and tool calls export as OpenTelemetry GenAI traces, which Jaeger, Tempo, Datadog and Langfuse can read.”
6. An open source safety layer for AI agent actions4 upvotes
An open-source safety layer adds monitoring and constraints to agent actions; it tags LangGraph executions for audit logs and human-in-the-loop gates.
source: “agent-control-standard,agent-security,agentic-ai,ai-agents,ai-safety,audit-log,human-in-the-loop,langgraph,llm,llm-security,mcp,mcp-server,model-conte”
7. Production-grade LangGraph template3 upvotes
Production-grade LangGraph template ships FastAPI, Docker, Helm, and Prometheus stubs so multi-step workflows reach production without starting from scratch.
source: “LangGraph, FastAPI, Docker, Helm, Terraform stubs, Prometheus metrics”
ActionRail grounds runtime values and actions to reduce semantic drift; LangGraph’s automatic tool discovery feeds the grounding framework during execution.
source: “LangGraph also has automatic tool discovery”
9. a2a cloud3 upvotes
a2a cloud turns a Python agent into a public web product with one command; it supports LangGraph agents so they become accessible without extra infra.
source: “Bring LangGraph, OpenAI Agents, CrewAI”
10. Runkite: Self-hosted Agent Control Plane1 upvotes
Runkite provides a self-hosted control plane for scheduling and permissioning multiple agents; its pluggable runner accepts LangGraph workflows directly.
source: “Pluggable runners (LangGraph, CrewAI, and more)”
What the data says
Computed from our index over the 10 products on this page; judgement fields are left blank where we cannot read them (methodology).
AutonomyL4 × 1 · L2 × 5 (6/10 judged)
Prerequisitesopen source × 8 · self-hostable × 5 · bring your own API key × 2
Common integrationsLanggraph × 10 · Crewai × 3 · MCP (Model Context Protocol) × 3 · LangChain × 2 · Opentelemetry × 2
In the index since2026-07-15 — 2026-09-15
Ranked by real traction from our index — not editorial picks, and no paid placement. Every judgement field requires a source quote; where we cannot read it, we leave it blank. Full criteria, thresholds and known limits: methodology.
Before you wire it up
Check whether the agent uses LangGraph’s native checkpointing and streaming or only calls it via an adapter. Verify the permission scope matches your data-residency rules, especially for self-hosted options like Charter or Runkite. Watch rate limits on tool calls inside the graph and test how the agent recovers from checkpoint restarts. Prefer agents whose quoted evidence shows direct LangGraph usage over incidental mentions.
FAQ
Which agents give me production tracing and persistence out of the box?
deepagents and the Production-grade LangGraph template expose LangGraph streaming and checkpointing directly; Charter adds OpenTelemetry export for the same graphs.
How do I add safety or loop control to an existing LangGraph workflow?
LoopGain supplies control-theory adapters and the open-source safety layer tags executions for audit and human gates without rewriting the graph.
Can I run LangGraph agents entirely on my own servers?
Charter, Runkite, and a2a cloud all support self-hosted or private-infra deployment of LangGraph workflows.