FirmFax prop firm data

Independent rule and fee data on 71 prop trading firms, every figure with its evidence state.

Should I use this

Quality & Safety

A
Description quality
87%
Schema completeness
85%
Naming quality
97%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Findings (2)

  • LOWTool 'get_firm' description lacks action verbin get_firm
  • LOWTool 'list_firms' description lacks action verbin list_firms

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~1,146Tokens (tool definitions)
~1.4 KBTypical response size
Moderate attention impact (0.90% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "prop-firm-data": {
      "url": "https://firmfax.com/api/mcp"
    }
  }
}

Remote endpoints

https://firmfax.com/api/mcpstreamable-http

What it can do

Tool inventory

Tools (6)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢get_firm(slug)

One prop trading firm. Every figure states whether we hold evidence for it, and a firm whose score range spans more than one band carries no letter grade at all.

Input Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "The firm slug, e.g. \"topstep\"."
    }
  },
  "required": [
    "slug"
  ]
}
🟢get_rule_changes(slug, since, kind, limit)

The dated record of what changed, newest first. Every entry states its KIND, and most of this tape is FirmFax correcting its own data rather than a firm changing its rules. Read counts before describing industry activity: a total taken across kinds overstates it.

Input Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "Limit to one firm. Omit for every firm."
    },
    "since": {
      "type": "string",
      "description": "ISO date, e.g. \"2026-08-01\". Entries dated on or after it."
    },
    "kind": {
      "type": "string",
      "enum": [
        "firm",
        "record",
        "withdrawn"
      ],
      "description": "firm = the firm changed a rule. record = FirmFax corrected its own data. withdrawn = we published an entry and then retracted it."
    },
    "limit": {
      "type": "number",
      "description": "How many entries to return, newest first. Default 50."
    }
  }
}
🟢get_evidence(slug, field)

The stored reading behind a figure: the verbatim quote, the page it came from, and the date we read it. Answers "we hold none" explicitly rather than returning an empty list. `outcome` is load-bearing: a `contradicted`, `contradiction` or `absent` row records what we read, not a figure we publish. Use get_firm for the published figure.

Input Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "The firm slug, e.g. \"topstep\"."
    },
    "field": {
      "type": "string",
      "description": "One field path, e.g. \"rules.dailyLossLimit\". Omit for every field we hold for this firm."
    }
  },
  "required": [
    "slug"
  ]
}
🟢find_firms(assetClass, maxActivationFee, maxResetFee, maxConsistencyPct, maxDailyLossLimit, ...)

Firms matching every criterion given. A firm whose record does not carry a criterion is never counted as a match and never silently dropped: it is returned separately under unknown, with the field that could not be tested. Absence is common here, so read counts before treating the matched list as the answer.

Input Schema

{
  "type": "object",
  "properties": {
    "assetClass": {
      "type": "string",
      "enum": [
        "forex",
        "futures",
        "crypto"
      ],
      "description": "Firms recorded as offering this. 21 of 71 records name no asset class and are returned as unknown."
    },
    "maxActivationFee": {
      "type": "number",
      "description": "Activation fee at or below this. 42 of 71 record no fee."
    },
    "maxResetFee": {
      "type": "number",
      "description": "Reset fee at or below this. 56 of 71 record no fee."
    },
    "maxConsistencyPct": {
      "type": "number",
      "description": "Consistency rule at or below this. 28 of 71 record none."
    },
    "maxDailyLossLimit": {
      "type": "number",
      "description": "Daily loss limit at or below this, in the unit dailyLossLimitUnit names. 31 of 71 record none."
    },
    "dailyLossLimitUnit": {
      "type": "string",
      "enum": [
        "percent",
        "usd"
      ],
      "description": "The unit maxDailyLossLimit is in. Daily loss limits are recorded in percent at some firms and in dollars at others, and the two are never compared: a firm recorded in the other unit is returned under unknown with its unit named."
    },
    "maxMinTradingDays": {
      "type": "number",
      "description": "Minimum trading days at or below this. 16 of 71 record none."
    },
    "maxMinDaysToPayout": {
      "type": "number",
      "description": "Minimum days to first payout at or below this, counted as minDaysToPayoutUnit names. 26 of 71 record none."
    },
    "minDaysToPayoutUnit": {
      "type": "string",
      "enum": [
        "calendar_days",
        "trading_days",
        "winning_days"
      ],
      "description": "What maxMinDaysToPayout counts: calendar_days, trading_days or winning_days. A wait is compared only with waits counted the same way; a firm counting another way, or stating no unit, is returned under unknown with what it counts named."
    },
    "minDaysToPayoutMinProfit": {
      "type": "number",
      "description": "With winning_days only: the profit a day must reach to count. A firm whose winning days carry a different profit bar is returned under unknown."
    }
  }
}
⚪compare_firms(a, b)

Two firms side by side. Reports each figure with its evidence state and whether the pair is comparable at all: a field neither firm records is not a tie, and a field only one records is not a win. No per-field winner is declared, because the direction of "better" for several of these is a judgement the published scoring model already makes; each firm's grade is returned alongside so the verdict comes from that model rather than from this tool.

Input Schema

{
  "type": "object",
  "properties": {
    "a": {
      "type": "string",
      "description": "First firm slug."
    },
    "b": {
      "type": "string",
      "description": "Second firm slug."
    }
  },
  "required": [
    "a",
    "b"
  ]
}
🟢list_firms

Every firm slug and name. Carries no figures, so nothing here needs evidence.

Input Schema

{
  "type": "object",
  "properties": {}
}

Community

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Evidence

Recent observations

verifiedversion not recorded6 tools
verifiedversion not recorded6 tools