| Ecosystem |
| 0 |
| 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 8 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes Twelve Data's real-time quote APIs through the Model Context Protocol (MCP), allowing AI agents to subscribe to live price feeds, bid-ask spreads, and volume data across equities, forex, crypto, and commodities. Implements MCP resource handlers that map financial data endpoints to standardized tool schemas, enabling LLMs to request current market snapshots without direct HTTP knowledge.
Unique: Bridges Twelve Data's financial APIs directly into the MCP ecosystem, allowing LLMs to treat market data as a native tool without custom HTTP orchestration; implements MCP resource handlers that abstract away API authentication and response parsing
vs alternatives: Simpler than building custom API integrations for each LLM framework; more specialized than generic HTTP tools because it understands financial data schemas and symbol formats natively
Provides access to Twelve Data's historical candlestick data (open, high, low, close, volume) across multiple timeframes (1-minute to monthly) for backtesting, analysis, and historical context in agent reasoning. Implements MCP tools that accept symbol, date range, and interval parameters, returning structured time-series arrays suitable for technical analysis or LLM context windows.
Unique: Exposes Twelve Data's multi-interval historical API through MCP, allowing agents to request specific date ranges and timeframes without managing pagination or API rate limits manually; abstracts away subscription-tier differences in data availability
vs alternatives: More flexible than static data exports because agents can request arbitrary date ranges on-demand; more cost-efficient than calling raw APIs repeatedly because MCP caching can reduce redundant requests
Implements MCP tools for searching and resolving financial instrument symbols across asset classes (stocks, ETFs, forex pairs, cryptocurrencies, indices) using Twelve Data's symbol search API. Returns standardized metadata including ISIN, exchange, country, and asset type, enabling agents to disambiguate user queries (e.g., 'Apple' → 'AAPL' on NASDAQ) and validate symbols before data requests.
Unique: Wraps Twelve Data's symbol search API as an MCP tool, allowing agents to resolve natural-language asset references into standardized symbols without custom parsing logic; includes metadata (ISIN, exchange, country) for context-aware filtering
vs alternatives: More reliable than regex-based symbol parsing because it queries an authoritative financial database; more user-friendly than requiring exact ticker input because it supports fuzzy search and disambiguation
Exposes Twelve Data's technical analysis API through MCP, enabling agents to request computed indicators (SMA, EMA, RSI, MACD, Bollinger Bands, ATR, etc.) for any symbol and timeframe without implementing indicator logic. Returns indicator values aligned with historical candles, allowing agents to reason about momentum, trend, and volatility in natural language.
Unique: Delegates technical indicator computation to Twelve Data's backend, eliminating the need for agents to import TA-Lib or implement indicator logic; returns pre-computed values aligned with historical data, reducing agent latency and complexity
vs alternatives: Faster than agents computing indicators locally because computation is server-side; more accurate than LLM-generated indicator logic because it uses battle-tested financial libraries
Provides MCP tools to query Twelve Data's corporate events API, returning upcoming earnings dates, dividend announcements, stock splits, and other material events for equities. Agents can check event calendars to contextualize market movements or avoid trading around high-volatility events.
Unique: Integrates Twelve Data's corporate events calendar into MCP, allowing agents to reason about material events without external calendar APIs; includes event metadata (type, date, value) for context-aware decision-making
vs alternatives: More integrated than requiring agents to query separate earnings/dividend APIs because events are unified in one tool; more reliable than web scraping because data comes from authoritative financial sources
Exposes Twelve Data's forex API through MCP, enabling agents to convert between currencies, fetch real-time and historical forex pair rates, and access bid-ask spreads for currency trading. Supports major pairs (EUR/USD, GBP/USD) and exotic pairs, with configurable intervals for technical analysis on currency movements.
Unique: Integrates Twelve Data's forex API into MCP, allowing agents to handle multi-currency operations natively; supports both real-time conversion and historical pair analysis without separate currency APIs
vs alternatives: More comprehensive than simple currency conversion APIs because it includes bid-ask spreads and historical data for trading; more reliable than static exchange rate tables because rates update in real-time
Provides MCP tools for querying Twelve Data's crypto API, including real-time prices, historical OHLCV data, and market cap information for cryptocurrencies across multiple exchanges. Agents can track crypto portfolios, analyze price movements, and reason about crypto market trends without external crypto-specific APIs.
Unique: Unifies crypto data from multiple exchanges through Twelve Data's API, allowing agents to compare prices and access historical data without managing exchange-specific APIs; treats crypto as a first-class asset class alongside equities and forex
vs alternatives: More integrated than separate crypto APIs because crypto data is unified with traditional financial data in one MCP interface; more reliable than exchange APIs directly because Twelve Data aggregates and normalizes data across sources
Implements the Model Context Protocol (MCP) server architecture, exposing Twelve Data financial APIs as standardized MCP tools with JSON schema definitions. Handles authentication (API key management), request/response serialization, error handling, and tool discovery, allowing any MCP-compatible client (Claude Desktop, custom LLM frameworks) to invoke financial data tools without custom integration code.
Unique: Implements a complete MCP server for Twelve Data, handling protocol details (JSON-RPC, schema validation, authentication) so clients don't need to manage API integration; provides standardized tool schemas that work across any MCP-compatible LLM framework
vs alternatives: More standardized than custom API wrappers because MCP is a protocol standard; more maintainable than embedding API calls in agent code because tool definitions are centralized and versioned
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 Twelve Data at 25/100.
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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