Allows direct HTTP requests to the Lambda Capture MCP server for macroeconomic semantic search.
Enables OpenAI's Responses API to perform semantic search on macroeconomic data using the Lambda Capture MCP server.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Lambda Capture MCP Server search for inflation expectations data"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP implementation of our standard Semantic Search API for Macroeconomic Data
Check server status HERE
from openai import OpenAI
client = OpenAI()
resp = client.responses.create(
model="gpt-4.1",
input="Key shifts in inflation expectations",
tools=[
{
"type": "mcp",
"server_label": "lambda-capture",
"server_url": "https://mcp.lambda-capture.com/v1/mcp/",
"headers": {
"Authorization": "Bearer YOUR_ACCESS_TOKEN"
}
}
]
)
print(resp.output_text)
curl -X POST "https://mcp.lambda-capture.com/v1/mcp/" \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-d '{
"jsonrpc": "2.0",
"method": "tools/call",
"id": 1,
"params": {
"name": "macroecon_semantic_search",
"arguments": {
"query_text": "inflation expectations",
"max_results": 3
}
}
}'
curl -X POST "https://mcp.lambda-capture.com/v1/mcp/" \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
-d '{
"jsonrpc": "2.0",
"id": "1",
"method": "list_tools",
"params": {}
}'Go to Claude -> Settings -> Developer -> Edit Config. Add the following to your claude_desktop_config.json
{
"mcpServers": {
"lambda-capture-mcp": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.lambda-capture.com/v1/mcp/",
"--header", "Authorization: Bearer YOUR_ACCESS_TOKEN"
],
"description": "RemoteMCP with Lambda Capture Macroeconomic Data API"
}
}
}Related MCP server: Crosmos MCP Server
for MCP Typescript: Node.js 18+ (includes npx and npm)
for MCP Python: Python 3.11+
Clone the repo
npm install to install the dependencies
npm run build to build the project
python -m venv .venv create virtual environment
source .venv/bin/activate activate virtual environment
pip install -r requirements.txt install the dependencies
Go to Claude -> Settings -> Developer -> Edit Config. Add the following to your claude_desktop_config.json
{
"mcpServers": {
"lambda-capture-mcp": {
"command": "node",
"args": [
"/Absolute Path to/mcp-server/dist/index.js"
],
"env": {
"LAMBDA_CAPTURE_API_KEY": "Your API Key string"
},
"description": "Runs the Node MCP with Lambda Capture Macroeconomic Data API"
}
}
}{
"mcpServers": {
"lambda-capture-mcp": {
"command": "/Absolute Path to/.venv/bin/python",
"args": [
"/Absolute Path to/mcp-server/main.py"
],
"env": {
"LAMBDA_CAPTURE_API_KEY": "Your API Key string"
},
"description": "Runs the Python MCP with Lambda Capture Macroeconomic Data API"
}
}
}Adjust maxTokens (.ts) or max_tokens (.py) variables, based on context window size of your model (doesn't count metadata, just content tokens)
© 2025 Lambda Capture Limited (Registration Number 15845351) 52 Tabernacle Street, London, EC2A 4NJ - All rights reserved
Perform semantic search on Macroeconomic Data Knowledge Base from Federal Reserve, Bank of England, and European Central Bank.
| Name | Required | Description | Default |
|---|---|---|---|
| query_text | Yes | The search query text (e.g., "Inflation expectations"). **required parameter**. | |
| score | No | Minimum relevance score threshold | |
| max_results | No | Maximum number of results to return | |
| type | No | Filter results by content type (text, table, or chart) or None for all | |
| source | No | Filter results by source institution or None for all | |
| start_date | No | Start date for filtering results (YYYY-MM-DD). If request needs recent/latest data, set start_date nearest to today up to 3 months ago. | 2018-01-01 |
| end_date | No | End date for filtering results (YYYY-MM-DD). if None, set to today - this is better for **most recent data**. default is today |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds value by specifying the data sources (Federal Reserve, Bank of England, European Central Bank), which is not in annotations. It does not contradict them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently communicates the tool's purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential purpose and data sources. With a self-explanatory name and schema covering all parameters, it is mostly complete, though it does not mention result format or pagination.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have clear descriptions in the input schema (100% coverage), so the tool description does not need to add extra parameter context. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (perform semantic search) and the resource (Macroeconomic Data Knowledge Base from three central banks). It is specific and distinguishes from any potential sibling tools, though none are listed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives, but the context of semantic search on macroeconomic data implies its use case. Without sibling tools, the lack of explicit when-not is less critical, but still a gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0macroecon_semantic_searchOnly one tool exists, so there is no possibility of confusion or ambiguity between tools.
With a single tool, naming consistency is not a concern; the name 'macroecon_semantic_search' is descriptive and follows a clear pattern.
Having only one tool feels thin for a server named 'Lambda Capture MCP Server', which implies broader functionality. While the tool is well-defined, the count is at the lower boundary of appropriateness.
The single tool adequately covers its intended purpose of semantic search on macroeconomic data. There are no obvious gaps for the stated functionality.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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