Comparison
Where OpenVesper fits relative to other tools you might be choosing between.
Last updated 2026-05. We try to keep this fair — if you spot something outdated or inaccurate, please open an issue.
Side-by-side
| Feature | OpenVesper | LangChain | Claude Code | OpenAI Assistants |
|---|---|---|---|---|
| Where state lives | Your disk (~/.openvesper/) | Your code | Your disk (.claude/) | OpenAI servers |
| Persistent runtime | Yes — gateway daemon | No — library | Yes — terminal session | Yes — Assistants API |
| Multi-LLM provider | 15 built-in | 30+ via integrations | Anthropic only | OpenAI only |
| Agent definition | Markdown (.agents/) | Python / TS code | Markdown (CLAUDE.md, AGENTS.md) | JSON via dashboard |
| Plugin / tool ecosystem | 51 bundled + your own | Hundreds via community | MCP servers | Function calling |
| Channel surface | CLI, Telegram, Slack, Discord, WS | Bring your own | Terminal only | API only |
| Cron / heartbeat | Built-in (cron.yaml) | Bring your own | Manual invocation | Bring your own |
| Self-hosted | Required | Yes | Yes | No |
| Pricing model | Free (LLM costs separate) | Free OSS (LangSmith $) | Per Claude usage | Per token |
| Telemetry | None | Opt-in | Opt-in | Always-on (their service) |
When to pick what
OpenVesper isn't the right answer for every problem. Some examples:
I want to chat with Claude in my terminal while coding
Claude Code is purpose-built for this. It integrates with your editor, your git history, your repo. OpenVesper can do it via REPL but it's not the focus.
I want to build a custom RAG app that ships in my product
LangChain (or LlamaIndex) has the deepest library of retrievers, vector store adapters, and embedding utilities. OpenVesper has plugin tools but doesn't bundle RAG primitives.
I want an agent that watches markets and pings me on Telegram
OpenVesper. The gateway runs persistently, heartbeats run on a cron schedule, channels (Telegram/Discord/Slack) are first-class, and crypto plugins (bagsfm, pumpfun, defi, onchain) are bundled.
I want to give my team a hosted assistant with managed memory
OpenAI Assistants or ChatGPT Team. OpenVesper deliberately doesn't ship a hosted version — it's software you run.
I want full data sovereignty (zero data leaves my hardware except the LLM call)
OpenVesper. State, audit logs, OAuth tokens, memory all stay on your disk. No telemetry. The LLM call is the only network boundary.
I want a Python notebook with 5 LLM calls and embeddings
LangChain is overkill. Use the Anthropic / OpenAI SDK directly. OpenVesper is overkill too.
What OpenVesper is not
Not a hosted SaaS. There is no openvesper.com account. If you want someone else to run the gateway for you, that's a different product someone else could build.
Not a replacement for Claude Code. If you're a developer spending most of your day in your editor and want pair-programming AI, Claude Code is built specifically for that workflow.
Not a RAG framework. LangChain and LlamaIndex have deeper coverage of vector stores, embedding models, document loaders. OpenVesper plugins can read PDFs and search the web, but it's not a RAG pipeline builder.
Not a multi-tenant product. The gateway is single-user by design. Bind it to loopback (default), keep your credentials local, your conversations local.
Not a trading bot. Bundled crypto plugins are read-only — they query data, they don't sign transactions. If you want a bot that trades, write a plugin that signs (the framework runs whatever you write), but the safety scaffolding is on you.
What we learned from each
From Claude Code: markdown is enough for agent persona. CLAUDE.md and AGENTS.md are convention; no DSL needed. We adopted the same shape for .agents/<mode>/.
From LangChain: a tool is just a function with a schema. We didn't reinvent that contract.
From OpenClaw: a persistent gateway beats one-shot CLI invocations. State lives in one place; channels are routes into it. Approval queue + audit log are non-negotiable.
From the JSON-schema / OpenAPI ecosystem: tool inputs are JSON Schema. No custom validators.
Got a tool you think should be on this page? Open an issue — we'll consider adding it if it changes the "when to pick what" decision for users.