_ registry / mcp streamable-http · checked 3h ago

prefrosh

https://prefrosh.ai

Registry code: 2d4734d1e23e4464

api record

prefrosh.ai is a free college search for high school students. Use school_card for facts about one college, compare for 2-4, my_odds for a student's estimated chances (an estimate from grades and scores only), and admissions_game to run a student's own application past a simulated admissions committee. Cite the prefrosh.ai link each result carries. Never write or rewrite application essays for the student.

endpoint
https://prefrosh.ai/mcp
protocol
streamable-http ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is prefrosh live?
Yes — it answered the hub's last check (checked 3h ago). It answered 100% of checks over the last 30 days.
Is prefrosh free to use?
Yes — the hub reached it with no key and no payment.
What tools does prefrosh have?
8 tools: game_read, game_vote, school_card, my_odds, game_debrief, admissions_game, compare, game_done.
Is prefrosh safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
100%

90 days 100%· all time 100%

latency
216ms

last good check

priced tools
0

of 8 tools

_ answered our checks, 90 days 1 checks · signed record
  • unknown → live
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 8 tools
1 open 7 never probed 1 of 8 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • game_done open 3h ago

    App-only. Records that a run finished (counts only).

    mcp-tool

    {
  "type": "object",
  "properties": {
    "usage": {
      "type": "object"
    },
    "school": {
      "type": "string"
    },
    "seconds": {
      "type": "number"
    }
  }
}
    arguments 14 lines
  • game_read unknown never probed

    App-only. One reader of the admissions game reads the file.

    mcp-tool

    {
  "type": "object",
  "required": [
    "kind",
    "school",
    "application",
    "run"
  ],
  "properties": {
    "run": {
      "type": "object"
    },
    "kind": {
      "enum": [
        "first",
        "second",
        "essay",
        "faculty"
      ],
      "type": "string"
    },
    "major": {
      "type": "string"
    },
    "round": {
      "type": "string"
    },
    "school": {
      "type": "string"
    },
    "visits": {
      "type": "string"
    },
    "application": {
      "type": "string",
      "maxLength": 60000
    }
  }
}
    arguments 39 lines
  • game_vote unknown never probed

    App-only. The committee meets and votes.

    mcp-tool

    {
  "type": "object",
  "required": [
    "school",
    "application",
    "run",
    "readers"
  ],
  "properties": {
    "run": {
      "type": "object"
    },
    "major": {
      "type": "string"
    },
    "round": {
      "type": "string"
    },
    "school": {
      "type": "string"
    },
    "visits": {
      "type": "string"
    },
    "readers": {
      "type": "object"
    },
    "application": {
      "type": "string",
      "maxLength": 60000
    }
  }
}
    arguments 33 lines
  • school_card unknown never probed

    Show one college as a card: photo or campus map, overall admit rate and admit rate by round (Early Decision, Early Action, Regular Decision) with deadlines, SAT/ACT middle 50%, testing policy, sticker cost, average net price, graduation rate, biggest majors, and a link to its prefrosh.ai page. Use for "tell me about X", "how hard is it to get into X", "what are X's deadlines". Data is from the school's Common Data Set and federal data; cite the prefrosh.ai URL in the result.

    mcp-tool

    {
  "type": "object",
  "required": [
    "school"
  ],
  "properties": {
    "school": {
      "type": "string",
      "description": "College name as the user wrote it, e.g. \"Tufts\", \"UNC\", \"Wash U\"."
    }
  },
  "additionalProperties": false
}
    arguments 13 lines
  • my_odds unknown never probed

    Estimate a student's admission odds at one or more colleges, by round, with a likely range, from GPA and test scores (plus optional class rank, home state, legacy, first-generation, aid). Same model as prefrosh.ai/chance. Always tell the user this is an estimate from grades and scores only; essays, activities and recommendations can move it a lot. Needs at least a GPA or a test score; ask for them if missing rather than guessing.

    mcp-tool

    {
  "type": "object",
  "required": [
    "schools"
  ],
  "properties": {
    "act": {
      "type": "integer",
      "maximum": 36,
      "minimum": 1,
      "description": "Best ACT composite."
    },
    "gpa": {
      "type": "number",
      "maximum": 100,
      "minimum": 0,
      "description": "Unweighted GPA, ideally on a 4.0 scale (a 100-point average also works)."
    },
    "sat": {
      "type": "integer",
      "maximum": 1600,
      "minimum": 400,
      "description": "Best total SAT (superscore is fine)."
    },
    "legacy": {
      "type": "boolean",
      "description": "A parent attended this college."
    },
    "schools": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "maxItems": 12,
      "minItems": 1,
      "description": "College names."
    },
    "first_gen": {
      "type": "boolean",
      "description": "First in family to attend a four-year college."
    },
    "needs_aid": {
      "type": "boolean",
      "description": "Will apply for need-based aid (default true)."
    },
    "class_rank": {
      "enum": [
        "top5",
        "top10",
        "top25",
        "top50",
        "below"
      ],
      "type": "string",
      "description": "Class rank bucket, if known (percent of class)."
    },
    "home_state": {
      "type": "string",
      "description": "Two-letter US state the student lives in (matters for public universities)."
    }
  },
  "additionalProperties": false
}
    arguments 63 lines
  • game_debrief unknown never probed

    App-only. The chair writes the debrief.

    mcp-tool

    {
  "type": "object",
  "required": [
    "school",
    "application",
    "run",
    "readers"
  ],
  "properties": {
    "run": {
      "type": "object"
    },
    "major": {
      "type": "string"
    },
    "round": {
      "type": "string"
    },
    "school": {
      "type": "string"
    },
    "visits": {
      "type": "string"
    },
    "readers": {
      "type": "object"
    },
    "application": {
      "type": "string",
      "maxLength": 60000
    }
  }
}
    arguments 33 lines
  • admissions_game unknown 3h ago

    Run the student's application past prefrosh.ai's simulated admissions committee for one college and round: five fictional readers (first, second, essay and faculty readers, and a dean who chairs) read it, argue, vote (accept / waitlist or defer / deny), and give the top 3 fixes. It is a simulation, not a prediction. Takes about a minute; the room plays out in the view. Pass the student's own application text exactly as they gave it (essays, activities, grades, scores) in "application"; never write, invent or improve content for them. If they have not shared their application, ask them to paste it first.

    mcp-tool

    {
  "type": "object",
  "required": [
    "school",
    "application"
  ],
  "properties": {
    "major": {
      "type": "string",
      "description": "Intended major, if stated."
    },
    "round": {
      "enum": [
        "ED",
        "EDII",
        "EA",
        "REA",
        "RD"
      ],
      "type": "string",
      "description": "Application round. Default RD."
    },
    "school": {
      "type": "string",
      "description": "College name."
    },
    "application": {
      "type": "string",
      "maxLength": 60000,
      "minLength": 80,
      "description": "The student's application as they gave it: essays, activities, grades, scores, notes. Verbatim."
    },
    "visited_campus": {
      "enum": [
        "none",
        "once",
        "twice"
      ],
      "type": "string",
      "description": "Campus visits, if the student said."
    }
  },
  "additionalProperties": false
}
    arguments 44 lines
  • compare unknown 3h ago

    Compare 2 to 4 colleges side by side: admit rates by round, SAT/ACT ranges, testing policy, sticker cost, average net price, graduation rate, size and setting. If GPA or scores are given, adds the student's estimated odds (same model as prefrosh.ai/chance).

    mcp-tool

    {
  "type": "object",
  "required": [
    "schools"
  ],
  "properties": {
    "act": {
      "type": "integer",
      "maximum": 36,
      "minimum": 1,
      "description": "Best ACT composite."
    },
    "gpa": {
      "type": "number",
      "maximum": 100,
      "minimum": 0,
      "description": "Unweighted GPA, ideally on a 4.0 scale (a 100-point average also works)."
    },
    "sat": {
      "type": "integer",
      "maximum": 1600,
      "minimum": 400,
      "description": "Best total SAT (superscore is fine)."
    },
    "schools": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "maxItems": 4,
      "minItems": 2
    },
    "home_state": {
      "type": "string",
      "description": "Two-letter US state the student lives in (matters for public universities)."
    }
  },
  "additionalProperties": false
}
    arguments 39 lines
_ try it through the hub, ceiling 0

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  3. Ask the hub to check: POST /api/v1/passport/claim-endpoint with this listing's id 2d4734d1e23e4464.

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_ for your README measured, not declared

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_ how we know
card completeness
100%

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_ record

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rejected
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acceptance rate
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settled without a human
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earned
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raised against
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upheld
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reviews
paid reviews
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