LinqAlpha MCP

curl --request POST \
  --url https://api.linqalpha.com/v1/mcp \
  --header 'Content-Type: application/json' \
  --header 'X-API-KEY: <api-key>' \
  --data '
{
  "jsonrpc": "2.0",
  "id": 123,
  "params": {}
}
'

import requests

url = "https://api.linqalpha.com/v1/mcp"

payload = {
    "jsonrpc": "2.0",
    "id": 123,
    "params": {}
}
headers = {
    "X-API-KEY": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-API-KEY': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({jsonrpc: '2.0', id: 123, params: {}})
};

fetch('https://api.linqalpha.com/v1/mcp', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.linqalpha.com/v1/mcp",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'jsonrpc' => '2.0',
    'id' => 123,
    'params' => [
        
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-API-KEY: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.linqalpha.com/v1/mcp"

	payload := strings.NewReader("{\n  \"jsonrpc\": \"2.0\",\n  \"id\": 123,\n  \"params\": {}\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("X-API-KEY", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.linqalpha.com/v1/mcp")
  .header("X-API-KEY", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"jsonrpc\": \"2.0\",\n  \"id\": 123,\n  \"params\": {}\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.linqalpha.com/v1/mcp")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["X-API-KEY"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"jsonrpc\": \"2.0\",\n  \"id\": 123,\n  \"params\": {}\n}"

response = http.request(request)
puts response.read_body

{
  "jsonrpc": "2.0",
  "id": 123,
  "result": {},
  "error": {
    "code": 123,
    "message": "<string>"
  }
}

MCP

LinqAlpha MCP

LinqAlpha MCP gives AI assistants direct access to institutional-grade financial data for fundamental research. Through the Model Context Protocol (MCP), your AI can query company fundamentals, earnings estimates, stock prices, economic indicators, SEC filings, and earnings transcripts — all from a single endpoint.

Supports JSON-RPC 2.0 protocol.

Available methods:

initialize — Initialize MCP session
ping — Health check
tools/list — List available financial data tools
tools/call — Execute a financial data tool

Setup (Claude Desktop):

{
  "mcpServers": {
    "linqalpha": {
      "url": "https://api.linqalpha.com/v1/mcp",
      "headers": { "x-api-key": "<your-api-key>" }
    }
  }
}

POST

mcp

LinqAlpha MCP

curl --request POST \
  --url https://api.linqalpha.com/v1/mcp \
  --header 'Content-Type: application/json' \
  --header 'X-API-KEY: <api-key>' \
  --data '
{
  "jsonrpc": "2.0",
  "id": 123,
  "params": {}
}
'

import requests

url = "https://api.linqalpha.com/v1/mcp"

payload = {
    "jsonrpc": "2.0",
    "id": 123,
    "params": {}
}
headers = {
    "X-API-KEY": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-API-KEY': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({jsonrpc: '2.0', id: 123, params: {}})
};

fetch('https://api.linqalpha.com/v1/mcp', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.linqalpha.com/v1/mcp",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'jsonrpc' => '2.0',
    'id' => 123,
    'params' => [
        
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-API-KEY: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.linqalpha.com/v1/mcp"

	payload := strings.NewReader("{\n  \"jsonrpc\": \"2.0\",\n  \"id\": 123,\n  \"params\": {}\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("X-API-KEY", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.linqalpha.com/v1/mcp")
  .header("X-API-KEY", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"jsonrpc\": \"2.0\",\n  \"id\": 123,\n  \"params\": {}\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.linqalpha.com/v1/mcp")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["X-API-KEY"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"jsonrpc\": \"2.0\",\n  \"id\": 123,\n  \"params\": {}\n}"

response = http.request(request)
puts response.read_body

{
  "jsonrpc": "2.0",
  "id": 123,
  "result": {},
  "error": {
    "code": 123,
    "message": "<string>"
  }
}

Overview

LinqAlpha MCP gives AI assistants direct access to institutional-grade financial data for fundamental research. Through the Model Context Protocol, your AI (Claude, Cursor, etc.) can query company fundamentals, earnings estimates, stock prices, economic indicators, SEC filings, and earnings transcripts — all from a single endpoint.

Quick Start

If you already have an existing API key, you must request a new key with MCP permissions enabled. Existing keys issued before the MCP endpoint release do not have MCP access. Contact support@linqalpha.com to request a new key.

Add the following to your MCP client configuration:

{
  "mcpServers": {
    "linqalpha": {
      "url": "https://api.linqalpha.com/v1/mcp",
      "headers": { "x-api-key": "<your-api-key>" }
    }
  }
}

claude mcp add linqalpha \
  --transport http \
  --url https://api.linqalpha.com/v1/mcp \
  --header "x-api-key: <your-api-key>"

{
  "mcpServers": {
    "linqalpha": {
      "url": "https://api.linqalpha.com/v1/mcp",
      "headers": { "x-api-key": "<your-api-key>" }
    }
  }
}

Use via Completion API

You can use LinqAlpha MCP tools directly from any LLM completion API (OpenAI, Anthropic, etc.) by making standard HTTP requests to our MCP endpoint. This lets you integrate LinqAlpha’s financial data tools into your own AI workflows and applications.

Step 1: List Available Tools

First, fetch the tool definitions to get their names and input schemas:

Python

import requests

MCP_URL = "https://api.linqalpha.com/v1/mcp"
HEADERS = {
    "Content-Type": "application/json",
    "x-api-key": "<your-api-key>"
}

# List all available tools
response = requests.post(MCP_URL, headers=HEADERS, json={
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/list",
    "params": {}
})

tools = response.json()["result"]["tools"]

Step 2: Convert to OpenAI Tool Format

Transform MCP tool definitions into the format expected by OpenAI’s API:

Python

def mcp_to_openai_tools(mcp_tools):
    """Convert MCP tool definitions to OpenAI function calling format."""
    openai_tools = []
    for tool in mcp_tools:
        openai_tools.append({
            "type": "function",
            "function": {
                "name": tool["name"],
                "description": tool["description"],
                "parameters": tool["inputSchema"]
            }
        })
    return openai_tools

openai_tools = mcp_to_openai_tools(tools)

Step 3: Chat with Tool Calling

Use the converted tools in your OpenAI completion request, then execute any tool calls against LinqAlpha MCP:

Python

from openai import OpenAI
import json

client = OpenAI()

messages = [
    {"role": "user", "content": "What was NVIDIA's revenue for the last 4 quarters?"}
]

# 1. Send request with tools
response = client.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    tools=openai_tools,
)

message = response.choices[0].message

# 2. If the model calls a tool, execute it via LinqAlpha MCP
if message.tool_calls:
    messages.append(message)

    for tool_call in message.tool_calls:
        # Execute tool call against LinqAlpha MCP
        mcp_response = requests.post(MCP_URL, headers=HEADERS, json={
            "jsonrpc": "2.0",
            "id": 1,
            "method": "tools/call",
            "params": {
                "name": tool_call.function.name,
                "arguments": json.loads(tool_call.function.arguments)
            }
        })

        tool_result = mcp_response.json()["result"]["content"][0]["text"]

        messages.append({
            "role": "tool",
            "tool_call_id": tool_call.id,
            "content": tool_result
        })

    # 3. Get final response with tool results
    final_response = client.chat.completions.create(
        model="gpt-4o",
        messages=messages,
        tools=openai_tools,
    )

    print(final_response.choices[0].message.content)

This pattern works with any LLM that supports function/tool calling — including Anthropic Claude API, Google Gemini, and open-source models. Just adapt the tool format conversion for your provider.

Available Tools

LinqAlpha returns an organization-specific tool contract through tools/list. The base contract currently contains 22 tools; approved organization capabilities can add tools such as RMS search and citation. Treat the live tools/list response as authoritative. Before planning a multi-tool workflow, call read_guide with orchestration/current. This guide is rendered from the authenticated organization’s current tool entitlement and routing policy.

Fundamentals & Estimates

Tool	Description
`fundamentals_data_query`	Query financial datasets including fundamentals, estimates, and ownership data
`fundamentals_data_docs`	Browse financial data schema documentation and available fields
`stock_prices`	Get historical and real-time stock price data

Economic Data

Tool	Description
`economic_data_query`	Query macroeconomic data (GDP, CPI, employment, Treasury yields, VIX, and more)
`economic_indicators`	List available economic indicators grouped by category
`economic_indicator_data`	Get economic indicator time series data (GDP, CPI, unemployment)
`economic_calendar`	Get upcoming economic data release schedule

Market Data

Tool	Description
`forex_rates`	Get foreign exchange currency pair rates and history
`commodity_prices`	Get commodity market data (energy, metals, grains, softs)
`treasury_rates`	Get US Treasury yield curve data across all maturities (1M-30Y)
`market_symbols`	List available market symbols for forex, commodities, and economic indicators
`market_risk_premium`	Get country-level market risk premium for CAPM calculations

Equity & Search

Tool	Description
`equity_database_query`	Query equity market database (stocks, events, documents)
`transcript_search`	Full-text search across earnings call transcripts and SEC filings. Requires a Manticore SQL query in the `sql` parameter (not natural language). Call `read_guide('data/manticore')` for the SQL dialect and schema

Research & Citations

Tool	Description
`cite_filing_source`	Create a citation for a filing/transcript excerpt found via `transcript_search`. Requires `chat_session_id` (from `create_research_session`) and `chunk_id` (the `id` field of a `transcript_search` result). This tool does not search — run `transcript_search` first
`cite_web_source`	Create a web-based research citation
`create_research_session`	Create a new research session for citation tracking
`get_citations`	Retrieve all citations created in the current research session
`web_search`	Search the web with date range filtering for recent financial news and analysis

Organization-specific RMS

These tools appear only when RMS access is included in the authenticated organization’s effective contract.

Tool	Description
`rms_search`	Search organization-internal research within the authenticated user’s RMS scope
`cite_rms_source`	Register an RMS result chunk as a citation in a research session

Platform

Tool	Description
`my_platform_data`	Query your organization’s LinqAlpha platform data
`list_guides`	List available financial data guides and documentation
`read_guide`	Read a specific financial data guide

Expanded data tools

The tables above are the core surface. An organization’s contract can also include further canonical tools — for example S&P Capital IQ (snp_query, snp_docs, snp_prices), LSEG (lseg_query), filings (filing_*, create_filing_reference), event transcripts (aiera_*), Korean market data (kr_*, kis_bond_*, koscom_etf_*, ecos_*, nice_*), prediction markets (kalshi_*, polymarket_*), and social or news sources (x_*, reddit_*, news_rss_search, search_naver_news). These tools keep their canonical names, and each tool’s description names the guide to read first; read that guide once before the first call. tools/list is the only authoritative inventory for your organization, and read_guide('orchestration/current') explains how the granted tools fit together. Tools that render inside the Linq web client or depend on customer-specific upstream credentials are never exposed here.

Protocol

This endpoint implements JSON-RPC 2.0 over HTTP, following the MCP specification.

Supported Methods

Method	Description
`initialize`	Initialize MCP session and receive server capabilities
`ping`	Health check
`notifications/initialized`	Client notification after initialization
`tools/list`	List all available tools with their input schemas
`tools/call`	Execute a tool with the given arguments

Example: List Tools

Request

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list",
  "params": {}
}

Response

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "tools": [
      {
        "name": "stock_prices",
        "description": "Get historical and real-time stock price data",
        "inputSchema": { ... }
      }
    ]
  }
}

Example: Call a Tool

Request

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "fundamentals_data_query",
    "arguments": {
      "sql": "SELECT ticker, revenue, net_income FROM financials WHERE ticker = 'AAPL' ORDER BY date DESC LIMIT 4"
    }
  }
}

Response

{
  "jsonrpc": "2.0",
  "id": 2,
  "result": {
    "content": [
      {
        "type": "text",
        "text": "Query returned 4 rows..."
      }
    ]
  }
}

Rate Limits

60 requests per minute per user
Exceeding the limit returns a JSON-RPC error with code -32000

Error Codes

Code	Meaning
`-32600`	Invalid JSON-RPC request or rejected identity/policy contract
`-32601`	Method not found
`-32602`	Invalid params (e.g., unknown tool name)
`-32603`	Internal server error
`-32000`	Rate limit exceeded

Authorizations

X-API-KEY

string

header

required

Body

application/json

jsonrpc

enum<string>

required

JSON-RPC version

Available options:

2.0

method

enum<string>

required

MCP method to invoke

Available options:

initialize,

ping,

notifications/initialized,

tools/list,

tools/call

integer

Request identifier

params

object

Method-specific parameters. For tools/call: { name: string, arguments: object }

Response

JSON-RPC 2.0 response

jsonrpc

enum<string>

Available options:

2.0

integer | null

Request identifier (null for error responses)

result

object

Method result (present on success)

error

object

Error object (present on failure)

Show child attributes

MCP

Basic

Analytics V2

Evaluations

RMS (On request)

Briefing

Sync Status

LinqAlpha MCP

Overview

Quick Start

Use via Completion API

Step 1: List Available Tools

Step 2: Convert to OpenAI Tool Format

Step 3: Chat with Tool Calling

Available Tools

Fundamentals & Estimates

Economic Data

Market Data

Equity & Search

Research & Citations

Organization-specific RMS

Platform

Expanded data tools

Protocol

Supported Methods

Example: List Tools

Example: Call a Tool

Rate Limits

Error Codes

Authorizations

Body

Response

​Overview

​Quick Start

​Use via Completion API

​Step 1: List Available Tools

​Step 2: Convert to OpenAI Tool Format

​Step 3: Chat with Tool Calling

​Available Tools

​Fundamentals & Estimates

​Economic Data

​Market Data

​Equity & Search

​Research & Citations

​Organization-specific RMS

​Platform

​Expanded data tools

​Protocol

​Supported Methods

​Example: List Tools

​Example: Call a Tool

​Rate Limits

​Error Codes

Authorizations

Body

Response

Overview

Quick Start

Use via Completion API

Step 1: List Available Tools

Step 2: Convert to OpenAI Tool Format

Step 3: Chat with Tool Calling

Available Tools

Fundamentals & Estimates

Economic Data

Market Data

Equity & Search

Research & Citations

Organization-specific RMS

Platform

Expanded data tools

Protocol

Supported Methods

Example: List Tools

Example: Call a Tool

Rate Limits

Error Codes