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Rank #9 of 13 in AI Coding Agents

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Conductor

YC S24 Built-in AI assistant

Melty Labs · commercial

conductor.build ↗Try it →
PA Score30/100AGENT-READY39/100BUILT-IN AI65/100API5/100
MCP✓CLI—API✓
no public signals
ArenasAI Coding Agents#9/13

Access

API docs ↗MCP docs ↗

Compare head-to-head

Codex logovs CodexClaude Code logovs Claude CodeCursor logovs CursorGitHub Copilot logovs GitHub CopilotGemini CLI logovs Gemini CLIOpenCode logovs OpenCodeDevin logovs Devinvs AiderCline logovs Clinecubic logovs cubicGoogle Antigravity logovs Google AntigravitySlate logovs Slate

Alternatives to Conductor →

Try itExperimental

See what an agent can do with Conductor before you ever sign up. Pick a story: recorded sessions replay real probe-harness transcripts; commands tagged live-capable can re-run against the real endpoint from our edge, right now (▶ run live — the exact same request, live and recorded lines always labeled); sandboxed self-drive sessions are designed and gated (docs/TRY-IT.md).

$curl -s https://www.conductor.build/docs/api/mcp.md | head -8recorded session — replayed, not live
recorded 2026-09-14 · exit 0 · captured verbatim by our probe harness, secrets redacted · pure-HTTP probe — ▶ run live re-runs it from our edge

Verified integrations

No integration evidence found in our corpus for this product yet — that means none was found, never that it doesn’t integrate.

By theme — the product's score on each story themeBy theme

Agenticness — how well agents can access and operate the productAgenticnessevidence →

How well agents can access and operate the product

38.8/100

Automation depth — how much of the product can run unattendedAutomation depthevidence →

How much of the product can run unattended

41.3/100

Autonomy agents — stories about autonomy agents in this arenaAutonomy agentsevidence →

Stories about autonomy agents in this arena

52.5/100

Code generation — quality of generated code — correctness, style, fit to the codebaseCode generationevidence →

Quality of generated code — correctness, style, fit to the codebase

42.5/100

Codebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understandingevidence →

How deeply the tool maps your repo — cross-file context, architecture awareness, history

11.3/100

Ecosystem — integrations, plugins, and third-party ecosystem storiesEcosystemevidence →

Integrations, plugins, and third-party ecosystem stories

15.8/100

Ide terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integrationevidence →

Meeting you in the IDE and terminal — extensions, inline flows, context

53.3/100

Openness — open source, data portability, and self-hosting storiesOpennessevidence →

Open source, data portability, and self-hosting stories

6.0/100

Pricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limitsevidence →

Free-tier ceilings, usage caps, and rate limits before you have to pay

46.0/100

Privacy posture — data-handling and privacy storiesPrivacy postureevidence →

Data-handling and privacy stories

0.0/100

Review safety — keeping generated changes safe — diffs, approvals, guardrailsReview safetyevidence →

Keeping generated changes safe — diffs, approvals, guardrails

31.2/100

Story verdicts — every judged story with its evidenceStory verdicts

What’s free: 0 free · 1 paid · 0 enterprise · 41 not stated in evidence

?

Sorted by importance (agentic first) (high → low) · 74/74 stories · click a row’s chevron for the rationale and evidence

Connect an agent via an official MCP server G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full8/10T

Delegate tasks to a built-in AI assistant inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full8/10X

Drive the product through a documented public API G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full7/10T

Plug MCP servers into this product so it can use their tools G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3none0/10

Point an agent at llms.txt or agent-oriented docs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full9/10T

Operate the product with natural-language commands G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10T

Set up automations that run autonomously in the background G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full7/10C

Run the product headlessly / in CI for automation G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial6/10T

Build against official SDKs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial5/10T

Get AI-generated insights and suggestions from my data inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial4/10C

Issue scoped/least-privilege API credentials for an agent G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial4/10X

Download a machine-readable API spec (OpenAPI or equivalent) G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Explore an interactive API reference with runnable examples G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Rely on versioned APIs with a documented deprecation policy G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Subscribe to events via webhooks G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Use an official CLI G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Test against a sandbox environment without touching production data G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness1partial6/10X

Have the agent stage changes, write commit messages, create branches, and open pull requests C

Pr review

developerReview safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety3full8/10X

Chat with the coding assistant directly inside my IDE for contextual help C

Ide integration

developerIde terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integration3full7/10X

Delegate longer-running coding tasks to run in the background in an isolated cloud environment C

Background execution

developerAutonomy agents — stories about autonomy agents in this arenaAutonomy agents3partialpaid7/10X

Run a coding agent locally from my terminal C

Terminal workflow

developerIde terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integration3partial7/10T

Turn a tracked issue into a complete pull request end-to-end C

Feature implementation

developerCode generation — quality of generated code — correctness, style, fit to the codebaseCode generation3full7/10C

Describe a feature or bug in plain language and have the agent implement or fix it across multiple files C

Feature implementation

developerCode generation — quality of generated code — correctness, style, fit to the codebaseCode generation3partial6/10X

Inspect diffs and run checks to catch problems before merging C

Pr review

developerReview safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety3partial6/10C

Reproduce issues, narrow down root causes, and verify fixes C

Issue diagnosis

developerCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding3partial6/10C

Define rules that trigger actions automatically on events G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth3partial5/10C

Have the agent write tests, fix lint errors, resolve merge conflicts, and update dependencies for me C

Maintenance automation

developerCode generation — quality of generated code — correctness, style, fit to the codebaseCode generation3partial5/10C

Add a project instructions file to set coding standards and conventions the agent follows C

Context management

developerCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding3partial4/10C

Export all of my data in open formats and leave G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3none0/10

Get automatic code review with contextual feedback on every pull request C

Pr review

developerReview safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety3none0/10

Have the agent map and explain an entire unfamiliar codebase without manually selecting context files C

Codebase mapping

developerCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding3none0/10

Prevent my data from being used to train AI models G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture3none0/10

Receive inline code completions and next-edit suggestions as I type C

Code completion

developerCode generation — quality of generated code — correctness, style, fit to the codebaseCode generation3n/a0/10

Self-host the core product G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3none0/10

Understand how a codebase fits together to find where to start making changes C

Codebase mapping

developerCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding3none0/10

Connect the agent to workflow tools like Jira, Slack, and Google Drive to extend its context C

Tool integration

developerEcosystem — integrations, plugins, and third-party ecosystem storiesEcosystem3noneuntestednone yet

Choose which underlying AI model powers my session from multiple providers C

Model choice

developerPricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limits2full8/10X

Manage multiple agent-driven coding sessions from one unified workspace C

Session management

engineering-leadIde terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integration2full8/10X

Review diffs visually and run multiple sessions side by side in a desktop app C

Session management

developerIde terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integration2full8/10T

Sign in with my existing product subscription plan to use the coding agent C

Authentication

developerPricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limits2full8/10C

Authenticate with an API key instead of an account login G

Authentication

developerPricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limits2full7/10C

Have a cloud agent build, test, and demo a feature end-to-end for my review C

Background execution

ai-native userAutonomy agents — stories about autonomy agents in this arenaAutonomy agents2full7/10C

Launch fleets of autonomous agents that work in parallel on different tasks for hours or days C

Parallel agents

ai-native userAutonomy agents — stories about autonomy agents in this arenaAutonomy agents2full7/10C

Perform bulk operations across many items at once G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2partial7/10C

Configure a reproducible cloud environment with the dependencies and setup steps my repository needs C

Background execution

developerAutonomy agents — stories about autonomy agents in this arenaAutonomy agents2partial6/10C

Run the agent non-interactively in scripts for workflow automation C

Terminal workflow

developerIde terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integration2partial6/10C

Schedule recurring jobs or workflows G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2full6/10C

Set up always-on agents that run on schedules or triggers to maintain and fix my software autonomously C

Scheduled automation

ai-native userAutonomy agents — stories about autonomy agents in this arenaAutonomy agents2partial6/10C

Start a task on one device and continue it later from another device or browser C

Cross device continuity

developerIde terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integration2partial6/10C

Control which external tools and integrations the agent is allowed to access C

Safe execution

engineering-leadReview safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety2partial5/10X

Debug issues and troubleshoot using natural-language queries C

Debugging

developerCode generation — quality of generated code — correctness, style, fit to the codebaseCode generation2partial5/10C

Do everything through the API that I can do in the UI G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2partial5/10T

Have the agent operate inside a sandbox when interacting with code, tools, and network resources C

Safe execution

engineering-leadReview safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety2partial5/10X

Kick off agent tasks directly from GitHub, GitLab, Linear, or Slack C

Tool integration

developerEcosystem — integrations, plugins, and third-party ecosystem storiesEcosystem2partial5/10C

Authenticate through an enterprise identity or cloud platform for compliance and scalability G

Authentication

engineering-leadPricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limits2none0/10

Choose where my data is stored (region/residency) G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2none0/10

Control data retention and deletion G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2none0/10

Have the agent build and recall memory automatically across sessions C

Context management

developerCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding2none0/10

Include multiple project directories in a single session for broader context C

Context management

developerCodebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding2none0/10

Opt out of telemetry and usage tracking G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2none0/10

Read the product's source under an open license G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2none0/10

Generate a working app from a sketch, image, or PDF design C

Multimodal generation

ai-native userCode generation — quality of generated code — correctness, style, fit to the codebaseCode generation2n/auntestednone yet

Get contextual explanations and automatic fixes for security vulnerabilities C

Security checks

developerReview safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety2n/auntestednone yet

Run several task attempts in parallel and compare results before choosing one C

Parallel agents

developerAutonomy agents — stories about autonomy agents in this arenaAutonomy agents1full8/10T

Integrate third-party partner-built agent apps into my workflows C

Marketplace

engineering-leadEcosystem — integrations, plugins, and third-party ecosystem storiesEcosystem1partial7/10X

Version, review, and roll back my automations G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth1partial6/10C

Create a shared workspace from my docs and repos as a common source of truth for the team C

Team knowledge

engineering-leadEcosystem — integrations, plugins, and third-party ecosystem storiesEcosystem1partial4/10C

Equip the agent with custom skills to perform specialized tasks C

Marketplace

developerEcosystem — integrations, plugins, and third-party ecosystem storiesEcosystem1none0/10

Let the tool automatically pick the best model for each task C

Model choice

developerPricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limits1none0/10

Opt out of having my code and prompts used for AI model training C

Data governance

engineering-leadReview safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety1none0/10

Sign in with a personal account to get free-tier access without managing API keys G

Authentication

developerPricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limits1none0/10

View interactive diffs and share selected code as context from within my JetBrains IDE C

Ide integration

developerIde terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integration1none0/10

Debug a live running web application directly from my coding assistant C

Debugging

developerCode generation — quality of generated code — correctness, style, fit to the codebaseCode generation1n/auntestednone yet

See license and public-code matching references for AI-suggested code C

Security checks

engineering-leadReview safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety1noneuntestednone yet

Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 52 stories with headroom

What would move Conductor’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.

  1. Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools

    nonemoves agent-readyimpact 45

    Evidence only shows Conductor exposing its OWN hosted MCP server so external MCP clients (ChatGPT, Claude, Codex) can manage Conductor's cloud workspaces (conductor-docs-14, conductor-probe-4) — the reverse direction of what the story asks.

  2. Codebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyUnderstand how a codebase fits together to find where to start making changes

    nonemoves PA Scoreimpact 30

    Conductor's evidence focuses on orchestrating parallel coding agents, worktrees, and workspace management, not on codebase comprehension features; the only related item is a basic file-content search (⌘⇧F), which does not constitute understanding how a codebase fits together or where to start making changes.

  3. Review safety — keeping generated changes safe — diffs, approvals, guardrailsGet automatic code review with contextual feedback on every pull request

    nonemoves PA Scoreimpact 30

    Conductor's evidence describes parallel agent orchestration, diffs, and human-facing review workflows (e.g., 'Conductor helps you review the diff, open a pull request' and PR comments loading from GitHub) but no automated code-review bot that posts contextual feedback on pull requests.

  4. Ecosystem — integrations, plugins, and third-party ecosystem storiesConnect the agent to workflow tools like Jira, Slack, and Google Drive to extend its context

    nonemoves PA Scoreimpact 30

    Evidence shows Conductor integrates with GitHub and Linear (issue/branch creation) and exposes an MCP server for managing cloud workspaces, but there is no mention of Jira, Slack, or Google Drive integrations anywhere in the docs or community evidence.

  5. Codebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyHave the agent map and explain an entire unfamiliar codebase without manually selecting context files

    nonemoves PA Scoreimpact 30

    Conductor's evidence focuses on orchestrating parallel agent workspaces, worktrees, git branches, and collaboration—not on any built-in whole-codebase mapping or explanation capability.

  6. Openness — open source, data portability, and self-hosting storiesExport all of my data in open formats and leave

    nonemoves PA Scoreimpact 30

    Conductor stores workspace state, chat history, and cloud workspace data, but no evidence in the pack shows an explicit data-export feature or open-format export guarantee; while code lives in git worktrees (inherently portable), there's no documentation of exporting chats, settings, or cloud workspace metadata.

  7. Openness — open source, data portability, and self-hosting storiesSelf-host the core product

    nonemoves PA Scoreimpact 30

    Conductor is a proprietary Mac app with a hosted cloud service and API/MCP server; there is no evidence of a self-hostable core product—no open-source repo, on-prem deployment option, or self-hosting docs are mentioned.

  8. Privacy posture — data-handling and privacy storiesPrevent my data from being used to train AI models

    nonemoves PA Scoreimpact 30

    No documentation or policy statement anywhere in the evidence pack addresses training-data opt-out or data-usage controls; in fact community reports explicitly note 'no way to find out if there's any data sent to your servers' and 'zero disclosure of data practices,' underscoring the absence of any such privacy control.

Showing the top 8 of 52 — every none/partial verdict in the story verdicts table is headroom.

Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.

Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map6 surfaces · 44 covered stories

Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.

docs38 stories

Changelog docs18 stories

Hacker News15 stories

llms.txt4 stories

OpenAPI spec3 stories

Markdown docs3 stories

Probe proofs — replayable recordings from the probe harnessProbe proofs

Replayable recordings from our probe harness — see the Prove-It protocol to submit one.

$curl -s https://www.conductor.build/docs/api/mcp.md | head -8reproduced
$ curl -s https://www.conductor.build/docs/api/mcp.md | head -8
---
title: "Conductor MCP server"
url: "/docs/api/mcp"
description: "Connect an MCP client to create and manage Conductor cloud workspaces"
---

# Conductor MCP server
proves: Point an agent at llms.txt or agent-oriented docsrecorded 2026-09-14
$curl -s https://www.conductor.build/llms.txt | head -4reproduced
$ curl -s https://www.conductor.build/llms.txt | head -4
# Conductor

> Conductor is a Mac app that lets you run many coding agents in parallel on your codebase.
proves: Point an agent at llms.txt or agent-oriented docsrecorded 2026-09-14
$curl -si -X POST https://api.conductor.build/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>'reproduced
$ curl -si -X POST https://api.conductor.build/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>'
HTTP/2 401

date: Mon, 14 Sep 2026 23:49:57 GMT

content-type: application/json; charset=utf-8

access-control-expose-headers: retry-after, X-Conductor-Request-Id

cf-cache-status: DYNAMIC

rndr-id: 17de285f-fcea-47a0

server: cloudflare

vary: Origin

vary: Accept-Encoding

www-authenticate: Bearer resource_metadata="https://api.conductor.build/.well-known/oauth-protected-resource/mcp", scope="mcp:tools"

x-conductor-request-id: 8f2ee26a724b5c3224c6f9739aca098e

x-render-origin-server: Render

nel: {"report_to":"cf-nel","success_fraction":0.0,"max_age":604800}

report-to: {"group":"cf-nel","max_age":604800,"endpoints":[{"url":"https://a.nel.cloudflare.com/report/v4?s=XDf94wrYtSSR6y0doi3F36GQQSAIwzTvE6EoL0rOv%2FNoahsprtToXXYsI5lECg8pf6WcFNHDaqdyOVWzf0VH%2BE%2BRm0alo6%2BMxdxryshGLfoQW%2BjdmY7Hblx4g3j%2FpKjtAFA2ZigK"}]}

cf-ray: a3b34a895e850dac-SJC

alt-svc: h3=":443"; ma=86400

{"jsonrpc":"2.0","error":{"code":-32001,"message":"Unauthorized"},"id":null}
proves: Connect an agent via an official MCP serverrecorded 2026-09-14

Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence

5 of 14 testable claims verified · 0 contradicted → integrity 36/100

20 distinct capability claims found in Conductor’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.

5

Verified

9

Unverified

0

Contradicted

30

Undersold

Verified (8)
Unverified (10)
Undersold (30)
Claims outside our story set (7)

Real capability claims found in Conductor’s own materials, but no story in this arena’s taxonomy covers them yet — that’s feedback on the taxonomy, not a mark against the product.

  • “Create private workspaces not shared with the rest of the team”

    source ↗

  • “Search file contents within a local project or cloud workspace”

    source ↗

  • “Edit attachments that are queued in messages before sending”

    source ↗

  • “Copy, save, download, or open images from chat previews”

    source ↗

  • “Enable exclusive port forwarding so only one workspace forwards ports at a time”

    source ↗

  • “Reassign a workspace to make a teammate responsible for it”

    source ↗

  • “Checkpoints let you revert code and chat state to an earlier turn in a session”

    source ↗
Suggest a story for these →

Business model

free-tiersubscription-flatsubscription-per-seatenterprise-custom

Free Mac app runs local parallel agents with your own keys/subscriptions; Pro $50/mo adds Conductor Cloud, API and multiplayer; Teams $60/user/mo; Enterprise custom.

pricing ↗

Score trend

How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.

PA Score31 (Sep 15 '26)30 (Sep 16 '26)
Agent-ready33 (Sep 15 '26)39 (Sep 16 '26)

Try Experimental

Run it in the microterminal →

Recorded agent sessions — and a live MCP handshake where the vendor ships one.

Flag

⚑ Flag a verdict

Think a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.

Badge

Embed this product's score badge →

Hotlinked SVG — always shows the live current score.

For agents

This page as markdown/llms.txt

Data

Evidence (JSON)Verdicts (JSON)