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Circlfi-MCP

by negm17111995
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JavaScript
Remote

CirclFi MCP Server

npm version MCP License: ISC

The official Model Context Protocol (MCP) server for CirclFi — the institutional-grade equity valuation platform.

Give any AI assistant direct access to 13 valuation models across 5,900+ US stocks, recalculated daily from SEC EDGAR, FRED, and GDELT data. Intrinsic values, Quality of Company scores (32 fundamental signals), and Value Trap risk scores — as native AI tools.

Two ways to connect

Option A — Remote server (no install, works everywhere)

Point any MCP-compatible client at the hosted endpoint:

https://circlfi.com/mcp

  • Transport: Streamable HTTP (stateless), current MCP spec

  • Auth: none needed for the free tier. Premium subscribers send their Gumroad purchase email as a bearer token: Authorization: Bearer you@example.com

  • Works with ChatGPT connectors (developer mode), Claude custom connectors (web/desktop), agent frameworks, and any cloud client that can't run local processes.

Option B — Local stdio server (npm)

npx -y circlfi-mcp

(Installing from GitHub also works: npx -y github:negm17111995/Circlfi-MCP)

Related MCP server: Toolstem MCP Server

Install in your client

Add to claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%\Claude\claude_desktop_config.json):

{
  "mcpServers": {
    "circlfi": {
      "command": "npx",
      "args": ["-y", "circlfi-mcp"],
      "env": { "CIRCLFI_EMAIL": "" }
    }
  }
}

Restart Claude Desktop and look for the tools icon. Premium subscribers: put your Gumroad purchase email in CIRCLFI_EMAIL.

claude mcp add circlfi -- npx -y circlfi-mcp

Or with premium access:

claude mcp add circlfi -e CIRCLFI_EMAIL=you@example.com -- npx -y circlfi-mcp

One-click install →

Or add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "circlfi": { "command": "npx", "args": ["-y", "circlfi-mcp"] }
  }
}
code --add-mcp '{"name":"circlfi","command":"npx","args":["-y","circlfi-mcp"]}'

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "circlfi": { "command": "npx", "args": ["-y", "circlfi-mcp"] }
  }
}

ChatGPT connects to remote MCP servers. In Settings → Connectors → Advanced → Developer mode, add a custom connector with the URL:

https://circlfi.com/mcp

  • Local: command npx, args ["-y", "circlfi-mcp"], optional env CIRCLFI_EMAIL

  • Remote: Streamable HTTP at https://circlfi.com/mcp, optional header Authorization: Bearer <gumroad-email>

Available tools

get_stock_valuation

Complete intrinsic valuation profile for any US ticker: fair value, implied upside, and statistical confidence per model, plus the Quality of Company (QOC) score and Value Trap risk score.

Free tier — 3 models, no signup: Bayesian DCF (10,000-run Monte Carlo with jump-diffusion), Earnings Power Value (Greenwald), CUCE Ensemble (meta-model).

Premium — all 13 models: the above plus EROIC Spread, First Chicago, Markov DDM, ML-RIV, Dynamic NAV, PWERM, Regime Cross-Sectional, Sentiment SOTP, FTNN Topology, and RCMH-DCF. Full methodology: circlfi.com/methodology

get_market_screener (Premium)

Screen all 5,900+ US stocks in one call. Filter by minimum QOC, maximum Value Trap score, or industry; return JSON for analysis or CSV for download.

Example prompts

  • "What is the intrinsic value of AAPL according to CirclFi?"

  • "Screen for Software stocks with QOC above 8 and Value Trap below 10, output as CSV."

  • "Compare the Bayesian DCF valuations of MSFT and GOOGL and tell me which trades further below fair value."

How it works (security & architecture)

This repository is a thin client — no proprietary algorithms, no API keys. Tool calls are forwarded to the CirclFi API (https://circlfi.com/api/mcp), which verifies premium subscriptions with Gumroad in real time and returns model output. Free-tier requests need no account at all. The hosted remote endpoint (https://circlfi.com/mcp) exposes the identical tools directly over Streamable HTTP.

All output is quantitative model data for educational purposes — not financial advice (disclaimer).

Pricing

  • Free: 3 models per stock, unlimited tickers

  • Premium ($39/mo or $299/yr): all 13 models + market screener — subscribe via Gumroad, then use your purchase email as CIRCLFI_EMAIL (local) or bearer token (remote)

Support

Open a GitHub Issue for server problems. For valuation methodology or subscription questions, see circlfi.com.

Available Tools

2 tools
get_market_screenerAInspect

Screen the entire stock market (5,900+ stocks) using CirclFi data. Requires a paid subscription. Can filter by QOC, ValueTrapScore, or Industry. Can return JSON or CSV format.

ParametersJSON Schema
NameRequiredDescriptionDefault
formatNoRequested format. CSV is recommended if you plan to provide a downloadable file to the user.
filtersNoOptional filters
fetchAllNoIf true, fetch the entire dataset of 5,900+ stocks without filtering.

TDQS

A3.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must cover behavioral traits. It mentions the subscription requirement but lacks details on rate limits, response size, pagination, data freshness, or any limits when using 'fetchAll'. Important behavioral context is missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences long, front-loading the main purpose and key details. Every sentence adds value with no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, but the description does not explain the return structure (JSON fields or CSV columns). It also lacks error handling or limit information. Given the complexity (3 params, nested object, fetching all data), it is incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the description adds value by recommending CSV for downloadable files. The parameters are well-documented in both schema and description, with the nested filter object clearly explained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool screens the entire stock market (5,900+ stocks) using CirclFi data, with specific filters and output formats. It distinguishes itself from the sibling tool 'get_stock_valuation' which focuses on individual stock valuation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions a required paid subscription and recommends CSV for downloadable files, providing some usage guidance. However, it does not explicitly contrast with the sibling tool or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_stock_valuationAInspect

Get the latest intrinsic valuation of a single stock from CirclFi's 13-model engine. Includes Bayesian DCF, EPV, ML-RIV, etc.

ParametersJSON Schema
NameRequiredDescriptionDefault
tickerYesThe stock ticker symbol (e.g., AAPL, MSFT)

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must disclose behavioral traits. It mentions 'latest' and includes model types but does not detail rate limits, caching, data freshness, or output format. Partial transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no fluff. Front-loaded with key info: verb, resource, source. Every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given low complexity (1 parameter, no output schema, no annotations), the description adequately covers what the tool does. Could mention output structure but not strictly necessary. Mostly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with parameter 'ticker' already well-described. Description does not add extra semantic value beyond the schema, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description uses specific verb 'Get' and resource 'latest intrinsic valuation of a single stock', names the engine 'CirclFi's 13-model engine', and lists example models. This clearly distinguishes from the sibling tool 'get_market_screener', which likely screens multiple stocks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description implies when to use (when wanting intrinsic valuation for one stock) but does not provide explicit guidance on when not to use or direct alternative to sibling. Lacks explicit usage conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updatesv1.1.0
    • First observedget_market_screener
    • First observedget_stock_valuation
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TDQS

A3.8/5.0

Scored across 2 tools

Disambiguation5/5

The two tools serve completely distinct purposes: one focuses on intrinsic valuation of a single stock, while the other screens the entire market. There is no overlap or potential for confusion.

Naming Consistency5/5

Both tools use a consistent 'get_' prefix followed by a descriptive noun phrase (get_stock_valuation, get_market_screener), following a clear verb_noun pattern.

Tool Count3/5

With only 2 tools, the server feels underpopulated for its stated domain of stock analysis and screening. While the tools are individually valuable, the scope suggests more tools would be reasonable (e.g., price data, fundamentals).

Completeness2/5

The server only covers valuation and market screening, leaving out essential stock analysis operations like price history, financial statements, or news. This is a significant gap for a stock analysis server.

Maintenance

ActivitySlowing
ResponsivenessNo issues

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