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Implements query validation against the connected database schema to prevent malformed queries, and handles result pagination/streaming for large datasets. Uses PostgreSQL's native client protocol (via node-postgres or similar) to maintain connection pooling and transaction semantics.","intents":["Execute ad-hoc SQL queries from an LLM agent without manual connection management","Fetch structured data from PostgreSQL and return it in a format the LLM can reason about","Stream large query results without loading entire datasets into memory","Validate query syntax against actual database schema before execution"],"best_for":["AI agents and LLM applications that need real-time database access","Teams building data-aware AI assistants that query production databases","Developers integrating PostgreSQL as a knowledge source for Claude or other MCP-compatible models"],"limitations":["No built-in query optimization or cost estimation — expensive queries can timeout or consume resources","Result streaming assumes MCP transport supports chunked responses; some clients may buffer entire result sets","No automatic parameterization of user inputs — relies on caller to prevent SQL injection","Transaction isolation level and connection pooling behavior depends on underlying PostgreSQL client configuration"],"requires":["PostgreSQL 10.0 or later","Node.js 16.0+","Valid PostgreSQL connection string (host, port, database, user, password)","MCP-compatible client (Claude Desktop, custom MCP host, etc.)"],"input_types":["SQL query string (SELECT, INSERT, UPDATE, DELETE, etc.)","Query parameters (optional, for parameterized queries)"],"output_types":["JSON-serialized result rows","Query metadata (row count, execution time, affected rows)","Error messages with SQL error codes"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocol-server-postgres__cap_1","uri":"capability://memory.knowledge.database.schema.introspection.and.exposure","name":"database schema introspection and exposure","description":"Automatically discovers and exposes PostgreSQL database schema (tables, columns, indexes, constraints, data types) as MCP resources that LLMs can inspect. Queries PostgreSQL's information_schema and pg_catalog system tables to build a schema model, then serializes it in a format the LLM can understand for query planning. Caches schema metadata to avoid repeated introspection queries.","intents":["Let an LLM understand the database structure before writing queries","Provide schema context to the LLM so it can generate correct table and column names","Expose foreign key relationships and constraints so the LLM can construct valid JOINs","Enable the LLM to discover available tables without manual documentation"],"best_for":["LLM agents that need to reason about database structure dynamically","Teams building natural-language-to-SQL systems","Developers who want LLMs to auto-discover available data without hardcoding schema"],"limitations":["Schema caching may become stale if database schema changes at runtime — requires manual refresh or TTL-based invalidation","Large schemas (100+ tables) may produce verbose context that consumes LLM token budgets","Does not expose row-level security policies or dynamic schema views","Introspection queries have performance cost on very large databases with thousands of tables"],"requires":["PostgreSQL 10.0+","SELECT permissions on information_schema and pg_catalog","Node.js 16.0+"],"input_types":["Database connection parameters","Optional schema filter (e.g., specific schema names to expose)"],"output_types":["JSON schema model with table definitions, column types, constraints","Markdown-formatted schema documentation","MCP resource list"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocol-server-postgres__cap_2","uri":"capability://tool.use.integration.parameterized.query.execution.with.type.safe.binding","name":"parameterized query execution with type-safe binding","description":"Supports parameterized SQL queries with placeholder binding (e.g., $1, $2 syntax) to prevent SQL injection attacks. Maps JavaScript/TypeScript types to PostgreSQL types and validates parameter types before execution. Uses the underlying PostgreSQL client's native parameterization support to ensure parameters are properly escaped and transmitted separately from query text.","intents":["Execute queries with user-supplied values safely without SQL injection risk","Bind variables from LLM-generated queries to prevent malicious input","Enforce type safety between application code and database parameters","Support prepared statements for repeated query execution with different parameters"],"best_for":["Production systems where LLMs generate SQL and must prevent injection attacks","Teams building secure AI agents that accept user input and query databases","Developers who need type-safe database access from TypeScript/JavaScript"],"limitations":["Parameter binding only works for values, not table/column names — dynamic schema references still require validation","Type coercion between JavaScript and PostgreSQL types may fail silently for edge cases (e.g., large integers beyond JavaScript Number precision)","Prepared statement caching is client-side only — no server-side prepared statement pooling across connections","No built-in rate limiting or query complexity analysis — malicious actors can still craft expensive queries with valid parameters"],"requires":["PostgreSQL 10.0+","Node.js 16.0+","Understanding of PostgreSQL parameterized query syntax ($1, $2, etc.)"],"input_types":["SQL query string with placeholders ($1, $2, ...)","Array of parameter values in order","Type hints (optional, for validation)"],"output_types":["Query result rows","Type validation errors","Execution metadata"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocol-server-postgres__cap_3","uri":"capability://tool.use.integration.transaction.management.and.isolation.control","name":"transaction management and isolation control","description":"Provides transaction control primitives (BEGIN, COMMIT, ROLLBACK) exposed as MCP tools, allowing LLM agents to group multiple queries into atomic operations. Supports configurable isolation levels (READ UNCOMMITTED, READ COMMITTED, REPEATABLE READ, SERIALIZABLE) and handles transaction state across multiple tool invocations. Implements automatic rollback on errors and connection cleanup.","intents":["Execute multiple related queries as a single atomic transaction","Ensure data consistency when an LLM agent performs multi-step operations","Prevent dirty reads or race conditions in concurrent scenarios","Rollback failed operations without manual cleanup"],"best_for":["LLM agents that perform multi-step data modifications (e.g., transfer funds, update related records)","Teams building financial or critical-data applications with AI","Developers who need ACID guarantees for LLM-driven database operations"],"limitations":["Transaction state is per-connection; if the MCP server restarts mid-transaction, uncommitted changes are lost","Long-running transactions can block other queries and hold locks — no automatic timeout or deadlock detection","Isolation level configuration is global per connection; cannot mix isolation levels within a single transaction","Nested transactions (SAVEPOINTs) may not be exposed, limiting partial rollback capability"],"requires":["PostgreSQL 10.0+","Node.js 16.0+","Understanding of ACID properties and transaction isolation levels"],"input_types":["Transaction control commands (BEGIN, COMMIT, ROLLBACK)","Isolation level specification","SQL queries to execute within transaction"],"output_types":["Transaction status (active, committed, rolled back)","Affected row counts","Error messages with rollback confirmation"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocol-server-postgres__cap_4","uri":"capability://automation.workflow.connection.pooling.and.resource.management","name":"connection pooling and resource management","description":"Manages a pool of PostgreSQL connections to avoid connection exhaustion and improve query latency. Implements connection lifecycle management (acquire, release, idle timeout, max pool size) and automatically handles stale or broken connections. Exposes pool metrics (active connections, queued requests, idle connections) for monitoring and debugging.","intents":["Handle multiple concurrent LLM queries without exhausting PostgreSQL connection limits","Reduce latency by reusing connections instead of creating new ones per query","Monitor connection pool health and detect resource leaks","Gracefully degrade under high load by queuing requests"],"best_for":["Production deployments with multiple concurrent LLM agents","Teams running the MCP server as a shared service for multiple clients","Developers who need to scale LLM-database interactions without overwhelming PostgreSQL"],"limitations":["Pool size must be configured upfront — no dynamic scaling based on load","Idle connections consume memory; aggressive timeout settings may cause connection churn","Connection pooling adds ~5-10ms latency per query compared to persistent connections","Pool metrics are in-memory only; no persistence or export for external monitoring systems"],"requires":["PostgreSQL 10.0+","Node.js 16.0+","Configuration of pool size, timeout, and idle thresholds"],"input_types":["Pool configuration (min/max size, idle timeout, connection timeout)","Database connection string"],"output_types":["Pool metrics (active/idle/queued connections)","Connection health status","Performance telemetry"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocol-server-postgres__cap_5","uri":"capability://tool.use.integration.error.handling.and.query.diagnostics","name":"error handling and query diagnostics","description":"Captures PostgreSQL errors (syntax errors, constraint violations, permission errors, etc.) and translates them into structured, LLM-friendly error messages. Includes query diagnostics like execution plans (EXPLAIN output), slow query detection, and error context (line number, error code). Provides suggestions for common errors (e.g., 'table not found' suggests available tables).","intents":["Help LLMs understand why a query failed and how to fix it","Provide diagnostic information for debugging complex queries","Detect and alert on slow or expensive queries","Suggest corrections for common SQL mistakes"],"best_for":["LLM agents that need to iterate on queries based on feedback","Teams building natural-language-to-SQL systems with error recovery","Developers debugging LLM-generated queries in production"],"limitations":["Error suggestions are heuristic-based and may not apply to all error types","EXPLAIN output can be verbose for complex queries, consuming LLM token budget","Slow query detection requires configurable thresholds; no automatic tuning","Error context is limited to PostgreSQL error codes and messages; application-level context is not captured"],"requires":["PostgreSQL 10.0+","Node.js 16.0+","Optional: EXPLAIN ANALYZE permissions for query planning"],"input_types":["Failed SQL query","PostgreSQL error message","Query execution context"],"output_types":["Structured error object with code, message, and context","Query execution plan (EXPLAIN output)","Suggested corrections or debugging steps","Performance metrics (execution time, rows scanned)"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-modelcontextprotocol-server-postgres__cap_6","uri":"capability://safety.moderation.read.only.mode.and.permission.enforcement","name":"read-only mode and permission enforcement","description":"Supports read-only mode that restricts the MCP server to SELECT queries only, preventing accidental or malicious data modifications. Enforces PostgreSQL role-based access control (RBAC) by connecting with a specific database user that has limited permissions. Validates query type (SELECT vs. DML) before execution and rejects write operations with clear error messages.","intents":["Run LLM agents against production databases without risk of data modification","Enforce least-privilege access by using a read-only database role","Prevent accidental DELETE or UPDATE queries from LLM agents","Audit which queries are executed by inspecting logs"],"best_for":["Production deployments where LLMs should only read data","Teams building data analytics or reporting agents","Developers who want to sandbox LLM database access"],"limitations":["Read-only mode is enforced at the MCP server level; determined LLMs could still attempt write queries (which will fail)","PostgreSQL RBAC is role-based, not row-level — cannot restrict access to specific rows or columns without additional views","Query type detection is pattern-based; complex queries with CTEs or subqueries may be misclassified","No built-in audit logging — relies on PostgreSQL's native logging for compliance"],"requires":["PostgreSQL 10.0+","Node.js 16.0+","PostgreSQL user with SELECT-only permissions","Configuration flag to enable read-only mode"],"input_types":["Read-only mode flag (true/false)","PostgreSQL user credentials with limited permissions","SQL query to validate"],"output_types":["Query validation result (allowed/rejected)","Error message if query is rejected","Execution result (for allowed queries)"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":22,"verified":false,"data_access_risk":"high","permissions":["PostgreSQL 10.0 or later","Node.js 16.0+","Valid PostgreSQL connection string (host, port, database, user, password)","MCP-compatible client (Claude Desktop, custom MCP host, etc.)","PostgreSQL 10.0+","SELECT permissions on information_schema and pg_catalog","Understanding of PostgreSQL parameterized query syntax ($1, $2, etc.)","Understanding of ACID properties and transaction isolation levels","Configuration of pool size, timeout, and idle thresholds","Optional: EXPLAIN ANALYZE permissions for query planning"],"failure_modes":["No built-in query optimization or cost estimation — expensive queries can timeout or consume resources","Result streaming assumes MCP transport supports chunked responses; some clients may buffer entire result sets","No automatic parameterization of user inputs — relies on caller to prevent SQL injection","Transaction isolation level and connection pooling behavior depends on underlying PostgreSQL client configuration","Schema caching may become stale if database schema changes at runtime — requires manual refresh or TTL-based invalidation","Large schemas (100+ tables) may produce verbose context that consumes LLM token budgets","Does not expose row-level security policies or dynamic schema views","Introspection queries have performance cost on very large databases with thousands of tables","Parameter binding only works for values, not table/column names — dynamic schema references still require validation","Type coercion between JavaScript and PostgreSQL types may fail silently for edge cases (e.g., large integers beyond JavaScript Number precision)","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0,"quality":0.24,"ecosystem":0.3,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.904Z","last_scraped_at":"2026-05-03T14:23:47.729Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":37,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-modelcontextprotocol-server-postgres","compare_url":"https://unfragile.ai/compare?artifact=npm-modelcontextprotocol-server-postgres"}},"signature":"3Ri272BNbWoiV/c5oWJMD+BmprwQ3NIbsa+1md1ufZfwzhc6+Q2+JtN5UJxKPUIkToR8wEFnYydrAZyxOUhyCQ==","signedAt":"2026-06-20T07:42:25.322Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-modelcontextprotocol-server-postgres","artifact":"https://unfragile.ai/npm-modelcontextprotocol-server-postgres","verify":"https://unfragile.ai/api/v1/verify?slug=npm-modelcontextprotocol-server-postgres","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}