BenchRank
#5 in AI Development PlatformsUpdated 2026-08

LobeHub

by LobeHub · Hosted multi-agent platform with a skills and MCP marketplace

BenchRank score

77.8 — BenchRank score out of 100

Screenshots of LobeHub

Homepage · LobeHub

Homepage of LobeHub

Overview

LobeHub is a hosted platform for running teams of AI agents. A "Chief Agent Operator" hires, schedules and reports on agents, which draw on a marketplace of skills and MCP servers and can be reached through Slack, Telegram or Discord. Plans allocate monthly compute credits, spent across models from Anthropic, OpenAI, Google, DeepSeek, xAI and others.

Best for
Individuals and small teams wanting to run several AI agents on a hosted, credit-metered platform
Pricing
Free tier with 500,000 monthly credits, then $12.9, $24.9 or $49.9 per month ($9.9, $19.9 or $39.9 per month billed annually), with an Enterprise Edition priced on request.
Runs on
WebiOSAndroidmacOSSelf-hostedCLI

Strengths and trade-offs

Strengths

  • Free tier with 500,000 monthly credits, no card required
  • Marketplace of 333,273+ skills and 83,764+ MCP servers
  • Agents reachable from Slack, Telegram and Discord
  • Bring your own provider API keys on every plan, including free

Trade-offs

  • Free tier blocks Claude and GPT-5 models and caps files at 10 MB
  • Usage is metered in credits, so heavy use needs paid top-ups
  • Headline $9.9–$39.9 rates need annual billing; monthly costs more
  • Enterprise pricing is not published — contact sales only

Pricing

Published plans and prices from LobeHub’s own pricing page.

How this score is made up

Each dimension is scored out of 100 and combined into the headline score using fixed weights.

  • MCP support

    Whether an agent can drive the product through the Model Context Protocol, and how much setup that takes.

  • API quality

    Public API surface: machine-readable spec, official SDKs, documented auth, errors, rate limits and versioning.

  • Documentation

    Publicly reachable docs — coverage, freshness, code samples and machine readability.

  • Agent friendliness

    How readable the site is to an automated client: llms.txt, structured data, server-rendered content, crawler access.

  • Pricing transparency

    Whether real prices are published, self-serve signup exists, and usage costs are knowable without a sales call.

  • Changelog

    A public, dated record of what shipped and when — the clearest signal that a product is still alive.

  • Marketing site structure

    Whether the site answers a buyer's questions: clear positioning, the pages that matter, and accessibility.

  • Page speed

    How fast the site loads for real visitors: Chrome UX Report 75th-percentile LCP, INP and CLS, with a Lighthouse mobile run standing in where a site has too little traffic for field data.

  • Operational trust

    Status page and incident history, security disclosure, compliance and data-processing documentation.

Measured, but not part of the score

Useful to know, but not a mark for or against the product — so these do not affect the ranking.

  • Openness

    Source availability, self-hosting, data export and open standards. Scored and shown, but not part of the composite — paid SaaS is not worse for being paid SaaS.

  • Maintenance

    Release cadence and repository activity. Scored and shown, but not part of the composite — it is only measurable for open repositories.

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Where this comes from

The LobeHub pages BenchRank reads when it scores the product — its documentation, release notes, status and security pages, and its repository where there is one.

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