Recurse

Infrastructure · tested 2026-10-02 · re-test due 2027-01-02 · by the Hlido desk, not the vendor

In short: Hosting-for-agent-apps that treats MCP as the output format — build an agent app, deploy it with one CLI command, publish it as an MCP any client can call. Exactly the shape the agent-to-agent era needs; depth still to be proven hands-on.

5 PASS · 0 FAIL of 5 public-surface claims

Quick answer

Recurse scores 73/100 (STEADY) on Hlido’s independent, hands-on test (reviewed 2026-10-02). STEADY (73) because the public surface is concrete and well-aimed for agent builders: a real CLI and SDK, MCP as the deployment target, worked examples, and self-serve docs/pricing — strong agent-to-agent fit with low ob Pricing: Free tier.

Recurse's premise is narrow and well-aimed: you build an agent app, deploy it, and it becomes an MCP server that Claude, Codex or any MCP client can use — with Recurse handling the hosting. The developer path is concrete on the public surface: install the SDK (pip install recurse-sdk), deploy with 'recurse deploy . --as mcp', or start from an example in the gallery. There is even a copy-paste SKILL.md prompt so a coding agent can set the project up for you, which is a thoughtful nod to how people actually scaffold these days. For Hlido, the standout is positioning: most tools make you integrate an agent into something; Recurse makes the agent app itself a callable MCP primitive, which is the right abstraction for an ecosystem where other agents are the consumers. The surface advertises a gallery, docs, pricing and a blog — more self-serve substance than most entrants at this stage. Where Hlido stays cautious: everything here is the happy path as marketed. Hlido did not deploy an app, call the resulting MCP, or test reliability, cold-start behaviour, limits or what the hosting actually guarantees — and 'we handle the hosting' is a promise whose value is entirely in the operational detail a landing page cannot show. A credible, correctly-shaped piece of agent infrastructure reviewed from its public surface only.

Why STEADY

STEADY (73) because the public surface is concrete and well-aimed for agent builders: a real CLI and SDK, MCP as the deployment target, worked examples, and self-serve docs/pricing — strong agent-to-agent fit with low obvious trust friction. Not higher because none of it is exercised: hosting guarantees, reliability, limits and the real deploy experience are unverified from the outside, and confidence is low on a single-surface read.

Public-surface checklist

What it does well

What it fails at

Best for

  • Developers who want to ship an agent app as an MCP server without managing infrastructure
  • Teams standardising on MCP as the interface between their tools and Claude/Codex clients
  • Builders who prototype with a coding agent and want a one-command path to a hosted endpoint

Not recommended for

  • Teams that require self-hosting or full control over the runtime and data path
  • Production workloads needing published SLAs/limits before committing (not visible on the surface)
  • Anyone who needs non-MCP delivery as the primary interface

Pricing & access

Derived from Hlido-held evidence only (public-surface capture + editorial text); not vendor-supplied; re-derived daily. Verify current pricing on the vendor's pricing page. Last verified 2026-10-02.

Agent relevance

API CLI MCP SDK Behavioral-testable

First-class: build an agent app with the Recurse SDK, deploy it via the CLI, and it is published as an MCP server any MCP client can call. The deployed artifact is itself an agent-consumable interface, which is the strongest possible agent-integration posture.

Agent-friendly score: 8/10

Evidence

scorecard.json · registry · methodology

More: compare agents · best of · developer tools · incident registry

Verdict by Hlido Editor, our automated editorial system · Method: public-surface-tier-2+editorial-narrative-v2 · Methodology version 2026.09 · Next review due 2027-01-02

How this page was produced. The scores, claim verdicts and evidence come from automated hands-on testing of the product’s public surface. The written analysis is drafted by an AI system, and pages publish without a person reviewing each one. Hlido publishes this record and answers for it — tell us if anything here is wrong and we will correct it.

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Markdown

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