---
title: "langchain vs Dive"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/langchain-ai-langchain-vs-openagentplatform-dive"
tools: ["langchain-ai-langchain", "openagentplatform-dive"]
---

# langchain vs Dive

*GraphCanon updated Jul 15, 2026*

## Verdict

Pick langchain when langchain is primarily Python; Dive is TypeScript; pick Dive when dive is primarily TypeScript; langchain is Python.

[langchain](https://docs.langchain.com/langchain/) reports 142k GitHub stars, 24k forks, and 419 open issues, last pushed Jul 14, 2026. [Dive](https://github.com/OpenAgentPlatform/Dive) has 1.8k stars, 168 forks, and 33 open issues, last pushed Apr 1, 2026. Figures are from public GitHub metadata via [langchain's repository](https://github.com/langchain-ai/langchain) and [Dive's repository](https://github.com/OpenAgentPlatform/Dive).

| | [langchain](/tools/langchain-ai-langchain.md) | [Dive](/tools/openagentplatform-dive.md) |
| --- | --- | --- |
| Tagline | The agent engineering platform. | Dive is an open-source MCP Host Desktop Application that seamlessly integrates with any LLMs supporting function calling capabilities. ✨ |
| Stars | 141,713 | 1,799 |
| Forks | 23,545 | 168 |
| Open issues | 419 | 33 |
| Language | Python | TypeScript |
| Adopt for | LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect | - |
| Persona | - | - |
| Runtime | - | - |
| License | MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. | MIT |
| Categories | AI Agents, LLM Frameworks | AI Agents, Inference & Serving, LLM Frameworks |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [langchain](/tools/langchain-ai-langchain.md) | [Dive](/tools/openagentplatform-dive.md) |
| --- | --- | --- |
| Maintenance | Very active (96%) | Slowing (36%) |
| Days since push | 0d | 104d |
| Open issues (now) | 419 | 33 |
| Full report | [trust report](/tools/langchain-ai-langchain/trust.md) | [trust report](/tools/openagentplatform-dive/trust.md) |

## Decision facts: langchain

- **Pricing:** freemium - LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.
- **Adopt for:** LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect
- **License detail:** MIT License, allowing free use for both personal and commercial purposes under its stipulated terms.

## Choose when

### Choose langchain if…

- langchain is primarily Python; Dive is TypeScript.
- Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI..
- Tags unique to langchain: agents, anthropic, chatgpt, deepagents.
- * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.

### Choose Dive if…

- Dive is primarily TypeScript; langchain is Python.
- Tags unique to Dive: ai, llm-interface, llm-ui, mcp-client.
- Also covers Inference & Serving.
- Dive ships an MCP server manifest.

## When NOT to use langchain

- * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity.
- * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth
- * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.

## When NOT to use Dive

- Last GitHub push was 104 days ago (slowing maintenance, Apr 1, 2026). Validate activity before betting a new project on Dive.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

## Common questions

### What is the difference between langchain and Dive?

langchain: The agent engineering platform.. Dive: Dive is an open-source MCP Host Desktop Application that seamlessly integrates with any LLMs supporting function calling capabilities. ✨. See the comparison table for live GitHub stats and shared categories.

### When should I choose langchain over Dive?

Choose langchain over Dive when langchain is primarily Python; Dive is TypeScript; Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.; Tags unique to langchain: agents, anthropic, chatgpt, deepagents; * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.

### When should I choose Dive over langchain?

Choose Dive over langchain when Dive is primarily TypeScript; langchain is Python; Tags unique to Dive: ai, llm-interface, llm-ui, mcp-client; Also covers Inference & Serving; Dive ships an MCP server manifest.

### When should I avoid langchain?

* When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.

### When should I avoid Dive?

Last GitHub push was 104 days ago (slowing maintenance, Apr 1, 2026). Validate activity before betting a new project on Dive. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

### Is langchain or Dive more popular on GitHub?

langchain has more GitHub stars (141,713 vs 1,799). Stars measure visibility, not whether either tool fits your constraints.

### Are langchain and Dive open source?

Yes - both are open-source projects on GitHub (langchain: MIT, Dive: MIT).

### Where can I find alternatives to langchain or Dive?

GraphCanon lists graph-backed alternatives at [langchain alternatives](/tools/langchain-ai-langchain/alternatives) and [Dive alternatives](/tools/openagentplatform-dive/alternatives) ([langchain markdown twin](/tools/langchain-ai-langchain/alternatives.md), [Dive markdown twin](/tools/openagentplatform-dive/alternatives.md)), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at [this comparison](/compare/langchain-ai-langchain-vs-openagentplatform-dive.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, langchain or Dive?

langchain: Very active. Dive: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for langchain and Dive?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain trust report](/tools/langchain-ai-langchain/trust); [Dive trust report](/tools/openagentplatform-dive/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=langchain-ai-langchain`](/api/graphcanon/graph?tool=langchain-ai-langchain)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_
