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Project IDX by Google logo
Project IDX by Google
✓ verifiedFree

Google's cloud-based, AI-assisted development environment, now rebranded and merged into Firebase Studio.

GitFluence logo
GitFluence
✓ verifiedFree

Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.

21K visits/mo
4.7K visits/mo
Pricing

No public pricing

No public pricing

No public pricing

DEVELOPER: FREE
STARTER: $119 / month
GROWTH: $599 / month
ENTERPRISE: Starting at $1,800 / month

No public pricing

Core features
  • Cloud-based IDE accessible from the browser
  • AI-assisted coding
  • Cross-platform app development
  • Preconfigured workspaces and templates
  • Now part of Firebase Studio
  • Natural-language to Git command suggestions
  • AI-driven command matching
  • Copy-ready command output
  • Git guides and reference
  • Developer-first platform for AI-powered integrations
  • Secure, isolated sandboxes for running JavaScript/Python code
  • Automatic management of npm/PyPI dependencies
  • Built-in platform plumbing: secrets, webhooks, scheduling, logs, and audit
  • Yep Agent (prompt → runnable processes)
  • MCP Server/Tools (convert code into AI agent tools)
  • Serverless runtime (YepCode Run) and SDK access
  • Zero-ETL data integration
  • Federated Query
  • Streaming Ingestion
  • Instant Replication with CDC
  • API to SQL conversion
  • NoSQL to SQL conversion
  • SQL to API conversion
  • Self-service Integration
  • Generate SQL with AI
Use cases
  • Building apps from anywhere in the browser
  • Prototyping with AI assistance
  • Developing cross-platform applications
  • Find the correct Git command quickly
  • Learn Git syntax by describing a goal
  • Avoid memorizing Git flags
  • Building complex API integrations that require custom code and logic beyond what no-code tools offer.
  • Safely running AI-generated scripts in isolated environments with secrets management.
  • Automating workflows that require large datasets, loops, branching, or custom dependencies.
  • Connecting AI agents to external databases, APIs, and services using MCP tools.
  • Query data directly from its source in real-time.
  • Process data wherever it is, blending data from different sources.
  • Ingest streaming data from Kafka, Segment, etc., into Peaka BI Table.
  • Replace nightly batch ingestion with real-time data access.
  • Treat every data source like a relational database by converting APIs to tables.
  • Use SQL to query NoSQL databases.
  • Query consolidated data and expose it with APIs.
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