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| Pricing | Free | Free |
| Capabilities | 9 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Fireproof implements a content-addressed immutable ledger architecture where all data mutations are appended as cryptographically signed entries rather than overwritten in-place. Each write operation generates a hash-verified ledger entry that chains to previous states, enabling full audit trails and tamper detection. The system uses IPFS-compatible content addressing (CIDv1) to store ledger blocks, allowing distributed replication and verification without a central authority.
Unique: Uses content-addressed immutable ledger with CIDv1 hashing and IPFS integration, enabling peer-to-peer replication and verification without requiring a central ledger authority — unlike traditional blockchain databases that require consensus mechanisms
vs alternatives: Provides cryptographic data integrity guarantees of blockchain systems without the consensus overhead, making it 10-100x faster for single-writer or trusted-writer scenarios than Ethereum or Hyperledger
Fireproof implements a real-time sync protocol that propagates ledger changes to connected peers using WebSocket or similar transports, with automatic conflict resolution through last-write-wins (LWW) semantics based on cryptographic timestamps. The sync engine maintains a vector clock per peer to track causality and prevent duplicate application of updates, while supporting offline-first operation where local mutations queue until connectivity resumes.
Unique: Combines immutable ledger with vector-clock-based causality tracking and last-write-wins resolution, enabling offline-first sync without requiring a central server to arbitrate conflicts — unlike traditional databases that require server-side conflict resolution
vs alternatives: Faster conflict resolution than CRDTs for simple LWW semantics (no need to merge complex data structures), but less sophisticated than CRDT-based systems for multi-user collaborative editing where all edits should be preserved
Fireproof exposes its immutable ledger and sync capabilities through the Model Context Protocol (MCP), allowing AI agents and LLMs to query, mutate, and subscribe to database changes using standardized MCP tools. The integration maps database operations (query, insert, update, delete) to MCP tool schemas with JSON-RPC transport, enabling Claude, other LLMs, and AI frameworks to treat Fireproof as a native tool without custom API wrappers.
Unique: Implements MCP as a first-class protocol for database access, allowing LLMs to directly query and mutate an immutable ledger with cryptographic verification — most databases require custom REST/GraphQL wrappers that lose the immutability guarantees
vs alternatives: Simpler integration than building custom API endpoints for each LLM, and maintains full audit trail of AI-initiated mutations unlike traditional databases where agent access is opaque
Fireproof stores ledger blocks using content-addressed hashing (CIDv1) compatible with IPFS, allowing ledger data to be stored on any IPFS node, S3-compatible storage, or local filesystem without vendor lock-in. The system uses merkle tree proofs to verify block integrity and enable peer-to-peer replication — any peer can independently verify that a block matches its content hash without trusting the source.
Unique: Uses CIDv1 content addressing with pluggable storage backends (IPFS, S3, filesystem), enabling true data portability and peer-to-peer replication without vendor lock-in — unlike traditional databases that couple data format with storage backend
vs alternatives: Provides IPFS-native storage without requiring a separate IPFS gateway or wrapper, and supports fallback to S3 or local storage for organizations not ready for full decentralization
Fireproof maintains queryable indexes (similar to database views) that are automatically updated as ledger entries are appended, with support for live subscriptions that push index changes to connected clients in real-time. Indexes are defined declaratively and rebuilt incrementally as new ledger entries arrive, avoiding full table scans for common query patterns.
Unique: Combines immutable ledger with incrementally-maintained indexes and live subscriptions, enabling efficient queries with real-time updates without requiring a separate query engine or pub/sub system
vs alternatives: More efficient than querying the raw ledger for every request, but less flexible than full SQL query engines — trades query expressiveness for predictable performance and automatic subscription support
Fireproof provides a client-side JavaScript library that maintains a local copy of the database in IndexedDB or similar browser storage, allowing applications to read and write data immediately without network latency. Mutations are queued locally and automatically synced to the server/peers when connectivity resumes, with automatic conflict resolution and deduplication to prevent duplicate writes.
Unique: Integrates offline-first local storage with automatic sync and conflict resolution, eliminating the need for developers to manually manage offline queues or implement sync logic — most databases require custom offline handling
vs alternatives: Simpler than implementing offline-first with Redux or other state management libraries, and maintains data consistency through cryptographic verification unlike ad-hoc offline solutions
Fireproof generates merkle tree proofs for any ledger entry or query result, allowing clients to cryptographically verify that data hasn't been tampered with without trusting the server. Proofs are compact (logarithmic in ledger size) and can be verified using only the root hash, enabling lightweight verification on resource-constrained devices.
Unique: Generates compact merkle tree proofs for any ledger entry without requiring clients to download the entire ledger, enabling lightweight verification on mobile and IoT devices — unlike blockchain systems that require full node downloads
vs alternatives: More efficient than blockchain verification for single-writer scenarios, and provides cryptographic guarantees without consensus overhead
Fireproof allows querying the database state at any point in history by replaying ledger entries up to a specific timestamp or ledger position. Queries execute against a point-in-time snapshot without requiring separate backups or snapshots — the immutable ledger itself serves as the complete history.
Unique: Enables time-travel queries by replaying the immutable ledger without requiring separate snapshots or backups — the ledger itself is the complete history, unlike traditional databases that require explicit backup/restore operations
vs alternatives: Simpler than managing separate backup snapshots, but slower than databases with built-in temporal tables or snapshot isolation for very large histories
+1 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.
Supabase scores higher at 42/100 vs Fireproof at 22/100.
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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