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API Reference

This document provides a complete reference for all API endpoints exposed by the pgEdge Natural Language Agent.

MCP JSON-RPC Endpoints

All MCP protocol methods are available via POST /mcp/v1:

initialize

Initializes the MCP connection.

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "initialize",
  "params": {
    "protocolVersion": "2024-11-05",
    "capabilities": {},
    "clientInfo": {
      "name": "pgedge-nla-web",
      "version": "1.0.0-alpha2"
    }
  }
}

tools/list

Lists available MCP tools.

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/list"
}

Response: 

{
  "jsonrpc": "2.0",
  "id": 2,
  "result": {
    "tools": [
      {
        "name": "query_database",
        "description": "Execute natural language queries against the database",
        "inputSchema": {
          "type": "object",
          "properties": {
            "query": {
              "type": "string",
              "description": "Natural language query"
            }
          },
          "required": ["query"]
        }
      }
    ]
  }
}

tools/call

Calls an MCP tool.

{
  "jsonrpc": "2.0",
  "id": 3,
  "method": "tools/call",
  "params": {
    "name": "query_database",
    "arguments": {
      "query": "How many users are there?"
    }
  }
}

resources/list

Lists available MCP resources.

{
  "jsonrpc": "2.0",
  "id": 4,
  "method": "resources/list"
}

resources/read

Reads an MCP resource.

{
  "jsonrpc": "2.0",
  "id": 5,
  "method": "resources/read",
  "params": {
    "uri": "pg://system_info"
  }
}

REST API Endpoints

GET /health

Health check endpoint (no authentication required).

Response: 

{
  "status": "ok",
  "server": "pgedge-postgres-mcp",
  "version": "1.0.0-alpha2"
}

GET /api/databases

Lists all databases accessible to the authenticated user.

Request: 

GET /api/databases HTTP/1.1
Authorization: Bearer <session-token>

Response: 

{
    "databases": [
        {
            "name": "production",
            "host": "localhost",
            "port": 5432,
            "database": "myapp",
            "user": "appuser",
            "sslmode": "require"
        },
        {
            "name": "analytics",
            "host": "analytics.example.com",
            "port": 5432,
            "database": "analytics",
            "user": "analyst",
            "sslmode": "require"
        }
    ],
    "current": "production"
}

Response Fields:

  • databases - Array of accessible database configurations
    • name - Unique name for this database connection
    • host - Database server hostname
    • port - Database server port
    • database - PostgreSQL database name
    • user - Database username
    • sslmode - SSL connection mode
  • current - Name of the currently selected database

Access Control:

  • Users only see databases listed in their available_databases configuration
  • API tokens only see their bound database (if configured)
  • In STDIO mode or with authentication disabled, all configured databases are visible

Implementation: internal/api/databases.go

POST /api/databases/select

Selects a database as the current database for subsequent operations.

Request: 

POST /api/databases/select HTTP/1.1
Content-Type: application/json
Authorization: Bearer <session-token>

{
    "name": "analytics"
}

Parameters:

  • name (required) - Name of the database to select

Success Response (200): 

{
    "success": true,
    "current": "analytics",
    "message": "Database selected successfully"
}

Error Responses:

Invalid request (400): 

{
    "success": false,
    "error": "Database name is required"
}

Database not found (404): 

{
    "success": false,
    "error": "Database not found"
}

Access denied (403): 

{
    "success": false,
    "error": "Access denied to this database"
}

API token bound to different database (403): 

{
    "success": false,
    "error": "API token is bound to a different database"
}

Notes:

  • Database selection is per-session (tied to the authentication token)
  • API tokens with a bound database cannot switch to a different database
  • Users can only select databases they have access to
  • The selected database persists for the duration of the session

Implementation: internal/api/databases.go

GET /api/user/info

Returns information about the authenticated user.

Request: 

GET /api/user/info HTTP/1.1
Authorization: Bearer <session-token>

Response: 

{
  "username": "alice"
}

Implementation: cmd/pgedge-pg-mcp-svr/main.go:454-511

POST /api/chat/compact

Smart chat history compaction endpoint. Intelligently compresses message history to reduce token usage while preserving semantically important context. Uses PostgreSQL and MCP-aware classification to identify anchor messages, important tool results, schema information, and error messages.

Request: 

POST /api/chat/compact HTTP/1.1
Content-Type: application/json

{
    "messages": [
        {"role": "user", "content": "Show me the users table"},
        {"role": "assistant", "content": "Here's the schema..."},
        ...
    ],
    "max_tokens": 100000,
    "recent_window": 10,
    "keep_anchors": true,
    "options": {
        "preserve_tool_results": true,
        "preserve_schema_info": true,
        "enable_summarization": true,
        "min_important_messages": 3,
        "token_counter_type": "anthropic",
        "enable_llm_summarization": false,
        "enable_caching": false,
        "enable_analytics": false
    }
}

Parameters:

  • messages (required): Array of chat messages to compact
  • max_tokens (optional): Maximum token budget, default 100000
  • recent_window (optional): Number of recent messages to preserve, default 10
  • keep_anchors (optional): Whether to keep anchor messages, default true
  • options (optional): Fine-grained compaction options
    • preserve_tool_results: Keep all tool execution results
    • preserve_schema_info: Keep schema-related messages
    • enable_summarization: Create summaries of compressed segments
    • min_important_messages: Minimum important messages to keep
    • token_counter_type: Token counting strategy - "generic", "openai", "anthropic", "ollama"
    • enable_llm_summarization: Use enhanced summarization (extracts actions, entities, errors)
    • enable_caching: Enable result caching with SHA256-based keys
    • enable_analytics: Track compression metrics

Response: 

{
    "messages": [
        {"role": "user", "content": "Show me the users table"},
        {"role": "assistant", "content": "[Compressed context: Topics: database queries, Tables: users, 5 messages compressed]"},
        ...
    ],
    "summary": {
        "topics": ["database queries"],
        "tables": ["users"],
        "tools": ["query_database"],
        "description": "[Compressed context: Topics: database queries, Tables: users, Tools used: query_database, 5 messages compressed]"
    },
    "token_estimate": 2500,
    "compaction_info": {
        "original_count": 20,
        "compacted_count": 8,
        "dropped_count": 12,
        "anchor_count": 3,
        "tokens_saved": 7500,
        "compression_ratio": 0.25
    }
}

Message Classification:

The compactor uses a 5-tier classification system:

  • Anchor - Critical context (schema changes, user corrections, tool schemas)
  • Important - High-value messages (query analysis, errors, insights)
  • Contextual - Useful context (keep if space allows)
  • Routine - Standard messages (can be compressed)
  • Transient - Low-value messages (short acknowledgments)

Implementation: internal/compactor/

Conversations API

The conversations API provides endpoints for managing chat history persistence. These endpoints are only available when user authentication is enabled.

GET /api/conversations

Lists conversations for the authenticated user.

Request: 

GET /api/conversations?limit=50&offset=0 HTTP/1.1
Authorization: Bearer <session-token>

Query Parameters:

  • limit (optional) - Maximum number of conversations to return (default: 50)
  • offset (optional) - Number of conversations to skip for pagination (default: 0)

Response: 

{
    "conversations": [
        {
            "id": "conv_abc123",
            "title": "Database schema exploration",
            "connection": "production",
            "created_at": "2025-01-15T10:30:00Z",
            "updated_at": "2025-01-15T11:45:00Z",
            "preview": "Show me the users table..."
        }
    ]
}

POST /api/conversations

Creates a new conversation.

Request: 

POST /api/conversations HTTP/1.1
Content-Type: application/json
Authorization: Bearer <session-token>

{
    "provider": "anthropic",
    "model": "claude-sonnet-4-20250514",
    "connection": "production",
    "messages": [
        {
            "role": "user",
            "content": "Show me the users table"
        },
        {
            "role": "assistant",
            "content": "Here's the schema for the users table..."
        }
    ]
}

Response (201 Created): 

{
    "id": "conv_abc123",
    "username": "alice",
    "title": "Show me the users table",
    "provider": "anthropic",
    "model": "claude-sonnet-4-20250514",
    "connection": "production",
    "messages": [...],
    "created_at": "2025-01-15T10:30:00Z",
    "updated_at": "2025-01-15T10:30:00Z"
}

GET /api/conversations/{id}

Retrieves a specific conversation.

Request: 

GET /api/conversations/conv_abc123 HTTP/1.1
Authorization: Bearer <session-token>

Response: 

{
    "id": "conv_abc123",
    "username": "alice",
    "title": "Database schema exploration",
    "provider": "anthropic",
    "model": "claude-sonnet-4-20250514",
    "connection": "production",
    "messages": [
        {
            "role": "user",
            "content": "Show me the users table",
            "timestamp": "2025-01-15T10:30:00Z"
        },
        {
            "role": "assistant",
            "content": "Here's the schema...",
            "timestamp": "2025-01-15T10:30:05Z",
            "provider": "anthropic",
            "model": "claude-sonnet-4-20250514"
        }
    ],
    "created_at": "2025-01-15T10:30:00Z",
    "updated_at": "2025-01-15T11:45:00Z"
}

PUT /api/conversations/{id}

Updates a conversation (replaces all messages).

Request: 

PUT /api/conversations/conv_abc123 HTTP/1.1
Content-Type: application/json
Authorization: Bearer <session-token>

{
    "provider": "anthropic",
    "model": "claude-sonnet-4-20250514",
    "connection": "production",
    "messages": [...]
}

Response: Same as GET response with updated data.

PATCH /api/conversations/{id}

Renames a conversation.

Request: 

PATCH /api/conversations/conv_abc123 HTTP/1.1
Content-Type: application/json
Authorization: Bearer <session-token>

{
    "title": "New conversation title"
}

Response: 

{
    "success": true
}

DELETE /api/conversations/{id}

Deletes a specific conversation.

Request: 

DELETE /api/conversations/conv_abc123 HTTP/1.1
Authorization: Bearer <session-token>

Response: 

{
    "success": true
}

DELETE /api/conversations?all=true

Deletes all conversations for the authenticated user.

Request: 

DELETE /api/conversations?all=true HTTP/1.1
Authorization: Bearer <session-token>

Response: 

{
    "success": true,
    "deleted": 15
}

Implementation: internal/conversations/

LLM Proxy Endpoints

The LLM proxy provides REST API endpoints for chat functionality. See the LLM Proxy Guide for detailed documentation on these endpoints:

  • GET /api/llm/providers - List configured LLM providers
  • GET /api/llm/models?provider=<provider> - List available models
  • POST /api/llm/chat - Send chat request with tool support

Schema Retrieval Examples

The get_schema_info tool is the primary method for discovering database structure. All examples in this section send requests to POST /mcp/v1 with Bearer token authentication.

Retrieving Table Schema

In the following example, the curl command retrieves schema information for a specific table:

curl -X POST http://localhost:8080/mcp/v1 \
    -H "Authorization: Bearer YOUR_TOKEN" \
    -H "Content-Type: application/json" \
    -d '{
        "jsonrpc": "2.0",
        "id": 1,
        "method": "tools/call",
        "params": {
            "name": "get_schema_info",
            "arguments": {
                "schema_name": "public",
                "table_name": "users"
            }
        }
    }'

The server returns a JSON-RPC response with TSV content:

{
    "jsonrpc": "2.0",
    "id": 1,
    "result": {
        "content": [
            {
                "type": "text",
                "text": "Database: mydb\n\nschema\ttable\t..."
            }
        ]
    }
}

Parsing TSV Responses in Python

In the following example, the parse_schema_tsv function converts the TSV response into structured data:

def parse_schema_tsv(tsv_text):
    """Parse get_schema_info TSV into structured data."""
    lines = tsv_text.strip().split("\n")
    # Skip header lines (non-TSV content)
    data_lines = [
        l for l in lines if "\t" in l
    ]
    if not data_lines:
        return []

    headers = data_lines[0].split("\t")
    rows = []
    for line in data_lines[1:]:
        values = line.split("\t")
        rows.append(dict(zip(headers, values)))
    return rows

# Usage
result = client.call_tool(
    "get_schema_info",
    {"schema_name": "public"}
)
tables = parse_schema_tsv(result)
for col in tables:
    print(
        f"{col['table']}.{col['column']}: "
        f"{col['data_type']}"
    )

Parsing TSV Responses in JavaScript

In the following example, the parseSchemasTsv function converts the TSV response into an array of objects:

function parseSchemasTsv(tsvText) {
    const lines = tsvText.trim().split("\n");
    const dataLines = lines.filter(
        l => l.includes("\t")
    );
    if (dataLines.length === 0) return [];

    const headers = dataLines[0].split("\t");
    return dataLines.slice(1).map(line => {
        const values = line.split("\t");
        const row = {};
        headers.forEach((h, i) => {
            row[h] = values[i] || "";
        });
        return row;
    });
}

Schema Retrieval Errors

The server returns an error when a schema does not exist or the user lacks permissions.

The following response indicates a missing schema:

{
    "jsonrpc": "2.0",
    "id": 1,
    "result": {
        "content": [
            {
                "type": "text",
                "text": "No tables found in schema 'missing'"
            }
        ],
        "isError": true
    }
}

A permission error occurs when the database user cannot access the requested schema:

{
    "jsonrpc": "2.0",
    "id": 1,
    "result": {
        "content": [
            {
                "type": "text",
                "text": "permission denied for schema restricted"
            }
        ],
        "isError": true
    }
}

Grant the required permissions to resolve access errors:

GRANT USAGE ON SCHEMA restricted TO your_user;
GRANT SELECT ON ALL TABLES IN SCHEMA restricted
    TO your_user;

Query Execution Examples

The query_database tool executes SQL queries in read-only transactions. The LLM client translates natural language queries to SQL before sending the request. Claude Desktop, the web client, and the CLI all support this translation.

Executing a SQL Query

In the following example, the curl command executes a SQL query against the selected database:

curl -X POST http://localhost:8080/mcp/v1 \
    -H "Authorization: Bearer YOUR_TOKEN" \
    -H "Content-Type: application/json" \
    -d '{
        "jsonrpc": "2.0",
        "id": 1,
        "method": "tools/call",
        "params": {
            "name": "query_database",
            "arguments": {
                "query": "SELECT id, name, email FROM users LIMIT 5"
            }
        }
    }'

The server returns the query results in TSV format:

{
    "jsonrpc": "2.0",
    "id": 1,
    "result": {
        "content": [
            {
                "type": "text",
                "text": "SQL Query: ...\n\nid\tname\n1\tAlice\n..."
            }
        ]
    }
}

Error Handling with Python

In the following example, the execute_query function includes retry logic and comprehensive error handling:

import requests
import json
import time

def execute_query(base_url, token, query,
                  max_retries=3):
    """Execute a query with error handling and retry."""
    headers = {
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json"
    }
    payload = {
        "jsonrpc": "2.0",
        "id": 1,
        "method": "tools/call",
        "params": {
            "name": "query_database",
            "arguments": {"query": query}
        }
    }

    for attempt in range(max_retries):
        try:
            response = requests.post(
                f"{base_url}/mcp/v1",
                headers=headers,
                json=payload,
                timeout=30
            )

            if response.status_code == 401:
                raise AuthError("Token expired")

            if response.status_code == 429:
                wait = 2 ** attempt
                time.sleep(wait)
                continue

            response.raise_for_status()
            result = response.json()

            if "error" in result:
                raise QueryError(
                    result["error"]["message"]
                )

            return result["result"]["content"][0]["text"]

        except requests.exceptions.Timeout:
            if attempt < max_retries - 1:
                time.sleep(2 ** attempt)
                continue
            raise

    raise Exception("Max retries exceeded")

Query Error Reference

The query_database tool returns specific errors for common failure conditions. The following table lists errors, their causes, and the recommended solutions:

Error Cause Solution
read-only transaction Write query Set allow_writes: true
relation does not exist Table missing Check table and schema
permission denied No grants Grant SELECT to user
syntax error Invalid SQL Fix the query syntax
query timeout Slow query Add indexes or simplify
connection refused DB offline Check host and port

Result Format

The query response follows a consistent structure for all results:

  • The server returns all query results in TSV format.
  • NULL values appear as empty strings in the output.
  • The first line of data contains the column headers.
  • Metadata lines precede the TSV data block.
  • The server truncates results at the configured row limit; the default is 100 rows.

For additional integration examples, see the Client Examples page. For details about available tools, see Tools Documentation.

See Also