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| Match Graph | 0 | 0 |
| Pricing | Paid | Free |
| Capabilities | 14 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Deploys Docker containers across 30+ geographic regions (Sydney to São Paulo) with automatic routing to edge infrastructure closest to end users. Uses a proprietary orchestration layer that provisions Micro VMs per container, manages networking across regions, and routes HTTP traffic based on geographic proximity. Supports framework-agnostic applications (Phoenix, Rails, Django, NextJS, Laravel, SvelteKit) by treating them as Docker artifacts.
Unique: Combines per-second billing granularity with automatic multi-region orchestration via proprietary Micro VM provisioning, eliminating need for manual region selection or load balancer configuration. Treats geographic distribution as a first-class feature rather than an add-on, with claimed sub-100ms latency from 18+ documented regions.
vs alternatives: Simpler than AWS Lambda@Edge or Cloudflare Workers for full application deployment because it runs complete Docker containers rather than function code, and cheaper than multi-region Kubernetes because it abstracts orchestration entirely.
Executes AI-generated or untrusted code in isolated hardware sandboxes called 'Sprites' with dedicated CPU, memory, networking, and filesystem per instance. Provides environment checkpointing and restoration capabilities, enabling rapid startup (claimed <1 second) and safe execution of code generated by LLMs without risking host system compromise. Each Sprite runs as a separate Micro VM with hardware-level isolation rather than container-level isolation.
Unique: Uses hardware-level VM isolation (Micro VMs) rather than container or process-level sandboxing, providing stronger isolation guarantees than Docker containers or gVisor. Combines rapid provisioning (<1 second claimed) with environment checkpointing, enabling both safety and performance for AI-generated code execution.
vs alternatives: More secure than in-process code execution or container sandboxing because hardware isolation prevents kernel exploits; faster than traditional VM sandboxes because Sprites checkpoint and restore environments rather than cold-booting; more practical than Firecracker or gVisor for production AI agent platforms because Fly.io manages the infrastructure.
Includes 'Accidental Deployments Are on the House' policy for paid support customers ($29/month minimum), waiving charges for unintended deployments or scaling events. Combines per-second billing granularity with billing safeguards to reduce surprise costs. Specific thresholds for what qualifies as 'accidental' and dispute resolution procedures are not documented.
Unique: Implements customer-friendly billing safeguards (accidental deployment waiver) as a differentiator, reducing billing friction and building trust with cost-conscious customers. Combines this with per-second billing transparency to create a more predictable cost model than competitors.
vs alternatives: More customer-friendly than AWS or GCP because it explicitly waives accidental charges; more transparent than competitors because per-second billing is granular; more supportive than self-service platforms because paid support includes billing dispute resolution.
Provides native integration with managed databases (CockroachDB, globally-distributed Postgres) and distributed systems (Elixir FLAME for distributed Erlang clusters) via private networking and coordinated deployment. Enables building multi-service architectures where databases and application clusters run on Fly.io infrastructure with automatic networking and encryption. Specific integration APIs and configuration mechanisms are not documented.
Unique: Provides native integration with specific databases and distributed systems (Cockroach, Postgres, Elixir FLAME) rather than treating them as external services, enabling coordinated deployment and automatic networking. Particularly strong for Elixir/Erlang applications via FLAME support.
vs alternatives: More integrated than using external managed database services because networking and deployment are coordinated; more suitable for distributed systems than generic cloud providers because it supports Elixir FLAME natively; more cost-efficient than separate database services because databases can run on Fly.io infrastructure.
Provides SSO integration for Fly.io account access and API authentication via narrowly-scoped tokens. Tokens can be restricted to specific organizations, applications, or operations, enabling fine-grained access control for CI/CD systems, third-party tools, and team members. Specific SSO providers and token scoping options not detailed.
Unique: Provides narrowly-scoped API tokens enabling fine-grained access control for CI/CD and third-party tools. Differentiates from cloud providers by emphasizing least-privilege token scoping.
vs alternatives: More granular than AWS IAM for API access (per-token scoping), simpler than managing SSH keys for multiple users, and more secure than sharing full account credentials
Fly's infrastructure is built on memory-safe Rust and Go, reducing vulnerability surface from memory corruption bugs. This architectural choice affects platform reliability and security but does not directly expose capabilities to end users. Mentioned as security differentiator but implementation details not provided.
Unique: Platform infrastructure built on memory-safe Rust and Go, reducing vulnerability surface from memory corruption bugs. Architectural choice rather than user-facing feature, but differentiates platform reliability.
vs alternatives: More secure than platforms built on C/C++ (memory safety), comparable to other modern cloud platforms using memory-safe languages, and reduces platform-level exploit risk
Charges for CPU and memory consumption on a per-second basis rather than hourly or monthly minimums, enabling cost-efficient scaling for variable workloads. Offers 40% discount on reserved capacity for predictable workloads, and includes 'Accidental Deployments Are on the House' policy for paid support customers to waive unintended charges. Pricing calculator available but specific per-second rates not documented.
Unique: Implements per-second billing granularity (vs hourly blocks common in AWS/GCP) combined with optional reserved capacity discounts, creating a hybrid model that rewards both variable and predictable workloads. Includes customer-friendly 'Accidental Deployments' waiver for paid support tiers, reducing billing friction.
vs alternatives: More cost-efficient than AWS EC2 hourly billing for short-lived workloads; more flexible than GCP's commitment discounts because per-second billing means no minimum commitment required; simpler than Kubernetes autoscaling cost optimization because billing is transparent and granular.
Provides automatic private networking between deployed applications and services (databases, caches, message queues) with end-to-end encryption enabled by default. Eliminates need for manual VPN configuration or public IP exposure. Supports integration with managed databases (Cockroach, globally-distributed Postgres) and distributed systems (Elixir FLAME, RPC systems, clustered databases) via private network connections.
Unique: Implements automatic end-to-end encryption for all private network traffic by default (not opt-in), eliminating the common misconfiguration where internal services communicate unencrypted. Integrates with Fly.io's multi-region infrastructure to provide seamless private networking across geographic regions.
vs alternatives: Simpler than Kubernetes NetworkPolicy or Istio service mesh because encryption is automatic and requires no configuration; more secure than manual VPN setup because it's enabled by default; more integrated than third-party service mesh tools because it's built into the platform.
+6 more capabilities
Executes SQL queries against Supabase PostgreSQL instances through the Model Context Protocol, translating natural language or structured query requests into parameterized SQL statements. Uses MCP's tool-calling interface to expose database operations as callable functions with schema validation, enabling LLM agents to perform CRUD operations, joins, and aggregations with automatic connection pooling and credential management through Supabase client SDK.
Unique: Exposes Supabase PostgreSQL as MCP tools with automatic credential injection from Supabase client SDK, eliminating manual connection string management and enabling seamless LLM-to-database queries within Claude or compatible agents
vs alternatives: Tighter integration than generic SQL MCP servers because it leverages Supabase's built-in authentication and connection pooling rather than requiring separate database credential configuration
Exposes Supabase Auth session state and user metadata through MCP tools, allowing agents to inspect current authentication context, retrieve user profiles, and trigger auth-related operations. Integrates with Supabase's JWT-based auth system to validate sessions and access user claims without re-authenticating, using the Supabase client's built-in session management.
Unique: Integrates Supabase's JWT-based auth system directly into MCP tool interface, allowing agents to inspect and act on auth state without managing separate credential stores or re-authentication flows
vs alternatives: More seamless than generic auth MCP servers because it leverages Supabase's built-in session management and avoids redundant credential passing between agent and auth system
Invokes Supabase Edge Functions (serverless TypeScript/JavaScript functions) through MCP tools, passing parameters and receiving results with optional streaming support. Uses Supabase's edge function HTTP API to trigger functions with automatic authentication headers and response parsing, enabling agents to execute custom business logic without embedding it in the agent itself.
Fly.io scores higher at 57/100 vs Supabase at 42/100. Fly.io leads on adoption and quality, while Supabase is stronger on ecosystem. However, Supabase offers a free tier which may be better for getting started.
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Unique: Exposes Supabase Edge Functions as MCP tools with automatic authentication and response parsing, allowing agents to invoke custom serverless logic without managing HTTP clients or credential injection
vs alternatives: More integrated than generic HTTP MCP tools because it handles Supabase-specific authentication, error handling, and response formatting automatically
Subscribes to real-time changes on Supabase tables through MCP's event streaming interface, using Supabase's PostgreSQL LISTEN/NOTIFY mechanism to push INSERT, UPDATE, and DELETE events to agents. Maintains persistent WebSocket connections and filters events by table and row-level policies, enabling agents to react to database changes without polling.
Unique: Bridges Supabase's PostgreSQL LISTEN/NOTIFY real-time system with MCP's tool interface, enabling agents to subscribe to database changes without managing WebSocket connections or event serialization
vs alternatives: More efficient than polling-based approaches because it uses Supabase's native real-time infrastructure rather than repeated database queries
Manages files in Supabase Storage buckets through MCP tools, supporting upload, download, list, and delete operations with automatic authentication and path-based access control. Uses Supabase's S3-compatible storage API with built-in support for public/private buckets and signed URLs for temporary access, enabling agents to handle file I/O without managing cloud storage credentials.
Unique: Exposes Supabase Storage's S3-compatible API as MCP tools with automatic authentication and signed URL generation, eliminating the need for agents to manage cloud storage credentials or generate temporary access tokens
vs alternatives: More integrated than generic S3 MCP tools because it leverages Supabase's built-in bucket policies and authentication rather than requiring separate AWS credentials
Performs semantic similarity searches on vector embeddings stored in Supabase PostgreSQL using pgvector extension, translating natural language queries into embedding vectors and executing cosine/L2 distance searches. Integrates with embedding providers (OpenAI, Cohere) or uses pre-computed embeddings, enabling agents to retrieve semantically similar documents or records without full-text search limitations.
Unique: Integrates pgvector directly into MCP tools with automatic embedding generation and distance calculation, enabling agents to perform semantic search without managing separate vector database infrastructure
vs alternatives: More efficient than external vector databases (Pinecone, Weaviate) for Supabase users because it colocates embeddings with relational data, reducing network latency and simplifying data synchronization
Exposes Supabase database schema information through MCP tools, allowing agents to discover table structures, column types, constraints, and relationships without manual schema documentation. Queries PostgreSQL information_schema and Supabase metadata tables to dynamically generate schema descriptions, enabling agents to construct valid queries and understand data relationships.
Unique: Queries Supabase's PostgreSQL information_schema directly through MCP tools, enabling agents to dynamically discover and adapt to database schemas without pre-configured schema definitions
vs alternatives: More flexible than static schema definitions because it reflects live database state, including recent migrations or schema changes
Enforces Supabase Row-Level Security policies within agent queries, ensuring that agents can only access rows permitted by RLS rules defined in the database. Evaluates policies based on authenticated user context (JWT claims, user ID) and applies WHERE clause filters automatically, preventing unauthorized data access at the database layer rather than application layer.
Unique: Delegates authorization enforcement to PostgreSQL RLS policies rather than implementing authorization in agent code, ensuring that data access rules are centralized and cannot be bypassed by agent logic
vs alternatives: More secure than application-level authorization because RLS is enforced at the database layer, preventing accidental data leaks even if agent code has bugs
+1 more capabilities