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Compare tools

Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Cody
✓ verifiedPaid

Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.

👁 245K/mo
Sherpa Coder
✓ verifiedFree

VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.

GitLoop
✓ verifiedFree trial

AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.

👁 11K/mo2.7K
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✓ verifiedFreemium

Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.

👁 775K/mo
exa.ai
✓ verifiedFreemium

Search, crawling and research API built for AI agents, with token-efficient results and structured web-data enrichment.

👁 761K/mo1.7K
Pricing
Enterprise: starting at $16K (includes AI feature credits, scales with team size)

No public pricing

No public pricing

Free trial available

No public pricing

Free: $0 (20,000 requests/mo)
Search: $7/1k requests
Contents: $1/1k pages
Deep Search: $12-15/1k requests
Monitors: $15/1k requests
Agent: $0.012-$1.00/run
Core features
  • Codebase-aware developer chat
  • AI code completions and inline edits
  • Customizable and shareable prompts
  • Automatic bug identification and debugging help
  • Context filters to exclude sensitive repos
  • Integrates with major code hosts and IDEs
  • in-editor chat with OpenAI assistants
  • workspace source-code context sharing
  • support for custom, user-defined assistants
  • secure management of the user's OpenAI account
  • Chat with your repositories
  • Natural-language codebase search
  • Fast code indexing
  • AI pull-request and commit review
  • Automated documentation generation
  • AI unit-test generation
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
  • Web search API tuned for agents
  • Full-page contents with token-efficient highlights
  • Asynchronous agents for deep research and enrichment
  • Structured outputs with grounded citations
  • Web monitors that track new events on a schedule
  • Zero data retention and SOC 2 Type II controls
Use cases
  • Engineers asking questions about an unfamiliar large codebase
  • Teams standardizing common coding tasks with shared prompts
  • Developers debugging errors faster with AI-assisted context
  • Enterprises running large-scale code migrations
  • getting coding help without switching out of VS Code
  • using a personalized OpenAI assistant tuned to a project
  • quick in-editor Q&A while writing code
  • Onboard new developers to a codebase
  • Resolve bugs faster
  • Generate docs and tests automatically
  • Review pull requests with AI
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
  • Give coding agents current docs and repo context
  • Power chatbots with real-time web answers
  • Enrich company and people data at scale
  • Monitor the web for fresh events
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