{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"neon-mcp-server","slug":"neon-mcp-server","name":"Neon MCP Server","type":"mcp","url":"https://github.com/neondatabase/mcp-server-neon","page_url":"https://unfragile.ai/neon-mcp-server","categories":["mcp-servers"],"tags":["neon","postgres","serverless","official"],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"neon-mcp-server__cap_0","uri":"capability://tool.use.integration.natural.language.to.neon.api.translation.with.mcp.protocol.bridging","name":"natural language to neon api translation with mcp protocol bridging","description":"Translates conversational requests into structured Neon API calls by mapping natural language intents to a pre-defined tool registry exposed via the Model Context Protocol. The system uses a layered architecture where LLM clients send text prompts, the MCP server parses tool invocations, and a Neon API client layer executes authenticated requests. This enables users to manage databases through conversation rather than direct API calls or CLI commands.","intents":["I want to ask Claude to create a new Neon project without learning the API","I need to let an LLM agent manage my database branches through natural language","I want to integrate database operations into my IDE's AI assistant workflow"],"best_for":["LLM application developers building database management agents","Teams using Claude Desktop or Cursor IDE who want database automation","Developers prototyping database workflows without writing boilerplate API code"],"limitations":["LLM must understand tool schemas correctly — complex multi-step operations may require explicit prompting","No built-in conversation memory — each request is stateless unless client maintains context","Tool invocation depends on LLM's function-calling capability — older models may fail to invoke tools reliably"],"requires":["MCP-compatible client (Claude Desktop, Cursor IDE, or custom MCP client)","Neon account with API key for authentication","Node.js 18.0.0 or higher for local deployment"],"input_types":["natural language text (conversational prompts)","tool invocation parameters (structured JSON from LLM)"],"output_types":["structured JSON responses from Neon API","natural language summaries of operations","error messages with remediation guidance"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_1","uri":"capability://tool.use.integration.dual.mode.transport.layer.with.stdio.and.sse.oauth.authentication","name":"dual-mode transport layer with stdio and sse/oauth authentication","description":"Implements two distinct deployment modes with different transport and authentication mechanisms: local mode uses stdio transport with API key authentication for IDE integration, while remote mode uses Server-Sent Events (SSE) with OAuth 2.0 for web-based clients. The architecture abstracts transport differences behind a unified MCP tool interface, allowing the same tool definitions to work across both modes. This enables developers to choose deployment based on security posture and client architecture.","intents":["I want to run the MCP server locally in my IDE with just an API key","I need to deploy the MCP server as a web service with OAuth authentication","I want the same database tools to work in both Claude Desktop and a web application"],"best_for":["Individual developers using Claude Desktop or Cursor IDE (local mode)","Teams deploying MCP servers as production web services with OAuth providers","Organizations requiring different auth mechanisms for dev vs production environments"],"limitations":["Local mode requires API key in environment — not suitable for untrusted environments","Remote mode requires OAuth provider setup (Google, GitHub, etc.) — adds operational complexity","SSE transport has connection timeout limits — long-running operations may require heartbeat management","No automatic mode switching — deployment mode must be chosen at startup"],"requires":["Node.js 18.0.0+","For local mode: Neon API key (NEON_API_KEY environment variable)","For remote mode: OAuth provider credentials and CORS-compatible client","MCP client supporting either stdio (local) or SSE (remote) transport"],"input_types":["environment variables (API keys, OAuth config)","HTTP requests with Bearer tokens (remote mode)","stdio JSON-RPC messages (local mode)"],"output_types":["JSON-RPC responses via stdio or SSE","OAuth redirect flows (remote mode)","structured tool responses"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_10","uri":"capability://safety.moderation.oauth.2.0.authentication.server.for.remote.mcp.deployment","name":"oauth 2.0 authentication server for remote mcp deployment","description":"Implements a built-in OAuth 2.0 server supporting multiple identity providers (Google, GitHub, etc.) for authenticating remote MCP clients. The implementation handles OAuth flows (authorization code, token refresh), manages user sessions, and issues access tokens that are validated on subsequent requests. This enables secure remote deployment of the MCP server without requiring users to manage API keys directly.","intents":["I want to deploy the MCP server as a web service with OAuth authentication","I need users to authenticate with their Google or GitHub account","I want to revoke access without changing API keys"],"best_for":["Teams deploying MCP servers as web services","Organizations using OAuth identity providers (Google, GitHub, etc.)","Applications requiring user-level access control"],"limitations":["OAuth provider setup is required — adds operational complexity","Token refresh requires additional API calls — may increase latency","No built-in user management — must be integrated with external identity provider","Session management is in-memory — not suitable for multi-instance deployments without shared state"],"requires":["OAuth provider credentials (client_id, client_secret)","Configured redirect URI matching deployment domain","HTTPS for production deployment (OAuth requires secure transport)"],"input_types":["OAuth provider configuration","authorization code from OAuth provider","refresh tokens"],"output_types":["access tokens (JWT format)","OAuth redirect responses","token validation results"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_11","uri":"capability://automation.workflow.observability.and.request.logging.with.structured.metrics","name":"observability and request logging with structured metrics","description":"Provides structured logging of all MCP tool invocations, including request parameters, execution time, and response status. The implementation logs to stdout in JSON format suitable for log aggregation systems, enabling monitoring of tool usage patterns and performance. Metrics include execution latency, error rates, and tool popularity, helping teams understand how the MCP server is being used and identify performance bottlenecks.","intents":["I want to monitor which database operations are being performed by LLMs","I need to track execution time for performance optimization","I want to debug tool invocation failures with detailed request/response logs"],"best_for":["Teams running MCP servers in production","DevOps engineers monitoring database automation workflows","Developers debugging tool invocation issues"],"limitations":["Logs are written to stdout — requires external log aggregation for persistence","No built-in metrics dashboard — metrics must be extracted from logs","Sensitive data (connection strings, query results) may be logged — requires log filtering","Log volume can be high for frequent tool invocations — may impact performance"],"requires":["Log aggregation system (ELK, Datadog, CloudWatch, etc.) for production use","JSON parsing capability in log aggregation system"],"input_types":["MCP tool invocations","execution context (timing, status)"],"output_types":["JSON-formatted log entries","structured metrics (latency, error_count, tool_name)","request/response summaries"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_2","uri":"capability://data.processing.analysis.sql.query.execution.with.connection.string.management.and.result.streaming","name":"sql query execution with connection string management and result streaming","description":"Executes arbitrary SQL queries against Neon databases by accepting SQL text, managing database connections through Neon's connection string API, and streaming results back to the client. The implementation handles connection pooling, error recovery, and result formatting (JSON, CSV, or raw). Queries are executed in the context of a specific Neon project and database, with optional branch selection for testing migrations before production deployment.","intents":["I want to run a SELECT query through Claude and get results as JSON","I need to execute a migration script on a test branch before applying it to production","I want to fetch connection strings dynamically for different database environments"],"best_for":["Data analysts querying Neon databases through LLM interfaces","Developers testing schema migrations on isolated branches","Teams automating database operations without direct SQL client access"],"limitations":["No transaction management — each query is auto-committed unless wrapped in BEGIN/COMMIT","Result streaming has memory limits — very large result sets may require pagination","No query optimization hints — LLM may generate inefficient queries without explicit guidance","Connection strings are ephemeral — must be refreshed for each query execution"],"requires":["Valid Neon project and database","Neon API key with database access permissions","SQL knowledge (LLM must generate valid PostgreSQL syntax)"],"input_types":["SQL text (SELECT, INSERT, UPDATE, DELETE, DDL statements)","project_id and database_name parameters","optional branch_id for isolated testing"],"output_types":["JSON array of result rows","CSV formatted results","raw PostgreSQL response with row count and execution time"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_3","uri":"capability://automation.workflow.neon.project.and.branch.lifecycle.management.through.api.automation","name":"neon project and branch lifecycle management through api automation","description":"Automates creation, deletion, and configuration of Neon projects and database branches by wrapping Neon's project management API. Supports operations like creating new projects, listing existing branches, creating test branches from production, and managing branch compute resources. The implementation maintains state consistency by validating project existence before operations and handling async branch creation workflows. This enables LLMs to provision isolated testing environments and manage multi-branch database architectures.","intents":["I want to create a new Neon project for a client without manual setup","I need to create a test branch from production to safely test schema changes","I want to list all branches in a project and their current status"],"best_for":["DevOps engineers automating database provisioning workflows","Development teams managing multiple database branches per project","LLM agents that need to create isolated testing environments on-demand"],"limitations":["Branch creation is asynchronous — may take 10-30 seconds to become available","No automatic branch cleanup — orphaned branches must be manually deleted or via scheduled jobs","Project deletion is irreversible — no soft-delete or recovery mechanism","Compute resource scaling requires separate API calls — not atomic with branch creation"],"requires":["Neon API key with project management permissions","Valid Neon account with billing configured","Understanding of Neon's project/branch/database hierarchy"],"input_types":["project_id (UUID)","branch_name (string)","parent_branch_id (optional, for branch creation)","compute_size parameters (optional)"],"output_types":["project metadata (id, name, region, created_at)","branch details (id, name, parent_id, compute_endpoint)","operation status (pending, ready, failed)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_4","uri":"capability://data.processing.analysis.database.schema.introspection.and.metadata.extraction","name":"database schema introspection and metadata extraction","description":"Retrieves database schema information (tables, columns, indexes, constraints) by querying PostgreSQL system catalogs through the SQL execution layer. The implementation caches schema metadata to reduce API calls and provides structured output suitable for LLM context windows. This enables LLMs to understand database structure before generating queries or migrations, improving query accuracy and preventing schema-related errors.","intents":["I want Claude to understand my database schema before writing queries","I need to get a list of all tables and their columns for documentation","I want to check if a column exists before generating an ALTER TABLE statement"],"best_for":["LLM agents that need schema awareness for query generation","Teams generating database documentation automatically","Developers validating schema changes before applying migrations"],"limitations":["Schema cache may become stale if external tools modify schema — no invalidation mechanism","Large schemas (1000+ tables) may exceed LLM context window limits","No support for schema versioning — only current schema state is available","Constraint and index information is limited to basic metadata"],"requires":["Read access to PostgreSQL system catalogs (pg_tables, pg_columns, etc.)","Valid database connection through Neon API"],"input_types":["project_id and database_name","optional table_name filter"],"output_types":["JSON schema representation (tables, columns, types, constraints)","formatted markdown documentation","raw PostgreSQL catalog queries"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_5","uri":"capability://automation.workflow.database.migration.workflow.with.branch.based.testing.and.rollback.safety","name":"database migration workflow with branch-based testing and rollback safety","description":"Orchestrates database migrations by creating isolated test branches, applying schema changes, validating results, and optionally promoting to production. The workflow uses Neon's branching to create a safe testing environment, executes migration SQL on the test branch, allows validation queries, and then applies the same migration to production only after confirmation. This pattern prevents production downtime by catching migration errors in isolation before they affect live databases.","intents":["I want to test a schema migration on a copy of production data before applying it","I need to safely add a new column with a default value without downtime","I want to validate that a migration doesn't break existing queries before deploying"],"best_for":["Teams managing schema changes in production databases","Developers using LLMs to generate and validate migrations","Organizations with strict change control requirements"],"limitations":["Migration validation is manual — no automatic compatibility checking","Large data migrations may timeout on test branches with limited compute","Rollback requires manual intervention — no automatic rollback on validation failure","Branch deletion is not automatic — test branches must be cleaned up separately"],"requires":["Neon project with at least one production branch","Write permissions to create test branches","SQL migration scripts (DDL statements)"],"input_types":["migration SQL text","validation query (optional)","project_id and branch_id"],"output_types":["test branch creation status","migration execution results","validation query results","promotion confirmation status"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_6","uri":"capability://data.processing.analysis.query.performance.analysis.and.optimization.recommendations","name":"query performance analysis and optimization recommendations","description":"Analyzes query performance by executing EXPLAIN ANALYZE on test branches and providing optimization recommendations. The implementation runs queries on isolated branches to avoid impacting production, collects execution plans, identifies bottlenecks (sequential scans, missing indexes), and suggests optimizations. This enables LLMs to understand query performance characteristics and propose index creation or query rewrites without manual profiling.","intents":["I want to understand why a query is slow before optimizing it","I need to identify missing indexes that would improve query performance","I want to compare query plans before and after adding an index"],"best_for":["Database performance engineers using LLMs for optimization","Teams automating index creation based on query analysis","Developers profiling queries during development"],"limitations":["EXPLAIN ANALYZE requires actual query execution — cannot analyze without running the query","Test branch data may not be representative — performance on small datasets may differ from production","Index recommendations are heuristic-based — may not be optimal for all workloads","No support for query plan comparison across multiple runs"],"requires":["Read access to target database","Ability to create test branches for safe analysis","SQL query to analyze"],"input_types":["SQL query text","project_id and branch_id","optional analysis parameters (sample size, timeout)"],"output_types":["EXPLAIN ANALYZE output (JSON or text)","performance metrics (execution time, rows scanned)","optimization recommendations (index suggestions, query rewrites)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_7","uri":"capability://tool.use.integration.connection.string.generation.and.credential.management","name":"connection string generation and credential management","description":"Generates database connection strings dynamically through the Neon API, supporting multiple connection formats (psql, JDBC, Node.js, Python) and authentication methods. The implementation retrieves credentials from Neon's API rather than storing them statically, ensuring credentials are always current and can be rotated without code changes. Connection strings are scoped to specific projects, databases, and branches, enabling fine-grained access control.","intents":["I want to get a connection string for my application without managing secrets","I need different connection strings for development, staging, and production","I want to rotate database credentials without updating application config"],"best_for":["Application developers integrating with Neon databases","DevOps teams managing database credentials across environments","Teams using LLMs to provision database access for applications"],"limitations":["Connection strings are ephemeral — must be refreshed periodically","No built-in credential rotation — rotation must be triggered externally","Connection pooling configuration is not included in generated strings","SSL/TLS options are limited to Neon's defaults"],"requires":["Neon API key with database access","Valid project_id, database_name, and optional branch_id"],"input_types":["project_id (UUID)","database_name (string)","branch_id (optional)","connection_format (psql, jdbc, nodejs, python, etc.)"],"output_types":["connection string (URI format)","structured connection parameters (host, port, user, password, database)","environment variable format (.env)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_8","uri":"capability://tool.use.integration.mcp.tool.schema.definition.and.llm.function.calling.integration","name":"mcp tool schema definition and llm function-calling integration","description":"Defines a comprehensive tool registry with JSON Schema descriptions for all database operations, enabling LLM clients to understand available tools and invoke them with proper parameters. The implementation uses OpenAI-compatible function calling format, allowing Claude, GPT-4, and other LLMs to automatically select and invoke appropriate tools based on user intent. Tool schemas include parameter validation, return type documentation, and usage examples suitable for LLM context windows.","intents":["I want Claude to understand what database operations are available and when to use them","I need the LLM to invoke the correct tool with proper parameters automatically","I want to document tool capabilities in a format that LLMs can understand"],"best_for":["LLM application developers building database agents","Teams integrating multiple tools into LLM workflows","Developers who want LLMs to autonomously select appropriate database operations"],"limitations":["Tool selection depends on LLM's understanding of schemas — complex tools may require explicit prompting","Schema descriptions must be concise to fit in context windows — detailed documentation is limited","No automatic schema validation — LLMs may invoke tools with invalid parameters","Tool discovery is static — new tools require server restart to expose"],"requires":["MCP-compatible LLM client (Claude, GPT-4, etc.)","Understanding of JSON Schema format","Tool definitions in OpenAI function-calling format"],"input_types":["tool definitions (JSON Schema)","parameter specifications","usage examples and descriptions"],"output_types":["MCP tool list response","JSON Schema definitions","function-calling format compatible with OpenAI API"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__cap_9","uri":"capability://safety.moderation.error.handling.and.recovery.with.structured.error.responses","name":"error handling and recovery with structured error responses","description":"Implements comprehensive error handling that catches Neon API errors, database connection failures, and SQL execution errors, then returns structured error responses with remediation guidance. The implementation distinguishes between recoverable errors (rate limits, temporary connection failures) and fatal errors (invalid credentials, schema errors), providing appropriate retry logic and user-facing error messages. This enables LLMs to understand what went wrong and suggest corrective actions.","intents":["I want the LLM to understand why an operation failed and suggest a fix","I need automatic retry logic for transient failures like rate limits","I want detailed error messages that help debug database issues"],"best_for":["LLM agents that need to handle failures gracefully","Teams building resilient database automation workflows","Developers debugging database integration issues"],"limitations":["Error messages are limited to what Neon API provides — some errors may be opaque","Retry logic is exponential backoff — may not be optimal for all failure modes","No automatic error recovery — LLMs must decide whether to retry","Error context is limited to the failed operation — no cross-operation error tracking"],"requires":["Proper error handling in MCP tool implementations","Structured error response format"],"input_types":["error objects from Neon API or database driver","operation context (tool name, parameters)"],"output_types":["structured error response (error code, message, remediation)","retry guidance (should_retry, retry_after_seconds)","human-readable error explanation"],"categories":["safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"neon-mcp-server__headline","uri":"capability://tool.use.integration.mcp.server.for.serverless.postgres.management","name":"mcp server for serverless postgres management","description":"The Neon MCP Server is an open-source tool that enables users to manage Neon PostgreSQL databases using natural language commands, simplifying database operations without needing to write SQL directly.","intents":["best MCP server for Postgres","MCP server for serverless database management","top tools for managing Neon databases","natural language database management solutions","MCP framework for PostgreSQL"],"best_for":["developers looking for serverless database solutions","teams needing natural language database interaction"],"limitations":[],"requires":["Neon account","MCP client"],"input_types":["natural language commands"],"output_types":["database management actions"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":75,"verified":false,"data_access_risk":"high","permissions":["MCP-compatible client (Claude Desktop, Cursor IDE, or custom MCP client)","Neon account with API key for authentication","Node.js 18.0.0 or higher for local deployment","Node.js 18.0.0+","For local mode: Neon API key (NEON_API_KEY environment variable)","For remote mode: OAuth provider credentials and CORS-compatible client","MCP client supporting either stdio (local) or SSE (remote) transport","OAuth provider credentials (client_id, client_secret)","Configured redirect URI matching deployment domain","HTTPS for production deployment (OAuth requires secure transport)"],"failure_modes":["LLM must understand tool schemas correctly — complex multi-step 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