PubSec Radar

Federal sales intelligence: expiring-contract triggers, agency spend intel, deal qualification.

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质量与安全性

A
描述质量
100%
模式完整度
100%
命名质量
88%
投毒风险
100%
权限匹配度
100%
协议合规性
100%

基于对工具定义和协议合规性的自动分析。

上下文开销

~1,600token 数(工具定义)
~2.4 KB典型响应大小
对注意力有中等影响(占 128k 上下文窗口的 1.25%)

这是每次将服务器的工具加载到模型上下文窗口时所消耗的大致 token 数。数值越高,可用于其他任务的注意力就越少。

安装

一键安装

将以下内容添加到你的 `claude_desktop_config.json` 文件中:

{
  "mcpServers": {
    "pubsec-sales-mcp": {
      "url": "https://pubsec-sales-mcp.kabrawala.workers.dev/mcp"
    }
  }
}

远程端点

https://pubsec-sales-mcp.kabrawala.workers.dev/mcpstreamable-http

它能做什么

工具清单

工具(5)

🟢 只读🟡 写入🔴 删除⚪ 未知
🟢find_expiring_contracts(agency, naics_code, window_days, limit)

Use this when prospecting or prepping a federal account and you want sales triggers: contracts at an agency that end soon, with the incumbent vendor, dollar values, and contracting office. Expiring contracts mean upcoming recompetes — the best time to displace an incumbent. Good queries name one agency and optionally a NAICS code, e.g. agency="DHS", naics_code="541512", window_days=90. Federal only (no state/local). Every response includes data-freshness and coverage caveats — read them; no data ≠ no spend.

输入模式

{
  "type": "object",
  "properties": {
    "agency": {
      "type": "string",
      "description": "Federal agency name, acronym, or code — e.g. \"DHS\", \"Department of Defense\", \"070\". Federal only; SLED is out of scope."
    },
    "naics_code": {
      "description": "Optional NAICS code to narrow by category, e.g. \"541512\" (computer systems design).",
      "type": "string",
      "pattern": "^\\d{2,6}$"
    },
    "window_days": {
      "default": 90,
      "description": "How far ahead to look for contract end dates, in days from today. Default 90, max 365.",
      "type": "integer",
      "minimum": 1,
      "maximum": 365
    },
    "limit": {
      "default": 15,
      "description": "Max contracts to return (top by obligated amount). Default 15.",
      "type": "integer",
      "minimum": 1,
      "maximum": 25
    }
  },
  "required": [
    "agency"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢agency_spend_profile(agency)

Use this to answer "what does this agency actually buy, and from whom?" before a first call: total contract obligations, 3-year trend, top 10 vendors, and top 10 NAICS categories for one fiscal year. Good queries name one agency, e.g. agency="HHS". Figures come from a daily snapshot of USAspending covering the current fiscal year plus a 3-year trend; freshness is stated in the response. Federal only. Read the coverage caveats — current-FY totals are partial-year and intel-agency spend is never published.

输入模式

{
  "type": "object",
  "properties": {
    "agency": {
      "type": "string",
      "description": "Federal agency name, acronym, or code — e.g. \"HHS\", \"Department of Veterans Affairs\", \"075\"."
    }
  },
  "required": [
    "agency"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢incumbent_lookup(vendor, agency, limit)

Use this to answer "who am I displacing and when?": a vendor name (plus optional agency scope) returns their current and recent awards with values and end dates, flagging awards that end within 12 months as displacement windows. Good queries use the vendor's registered name or a distinctive fragment, e.g. vendor="Booz Allen", agency="DHS". Federal only. Zero results ≠ no presence — check the caveats for name-matching tips.

输入模式

{
  "type": "object",
  "properties": {
    "vendor": {
      "type": "string",
      "minLength": 2,
      "description": "Vendor/incumbent name as registered in federal awards, e.g. \"Booz Allen Hamilton\", \"CACI\". FPDS matches it as a phrase — shorter fragments match more."
    },
    "agency": {
      "description": "Optional federal agency to scope the lookup, e.g. \"DHS\". Omit to search government-wide.",
      "type": "string"
    },
    "limit": {
      "default": 15,
      "description": "Max awards to return (largest first). Default 15.",
      "type": "integer",
      "minimum": 1,
      "maximum": 25
    }
  },
  "required": [
    "vendor"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟡generate_discovery_questions(agency, product_category, naics_code, meeting_context)

Use this when prepping a meeting with a federal agency: it returns discovery questions tuned to public-sector selling (fiscal-year timing, contract vehicles, FedRAMP/ATO, incumbents), grounded in the agency's live spending data where possible — each data-backed question cites the number that motivated it with a source URL. Good queries name the agency, what you sell, and the meeting type, e.g. agency="DHS", product_category="zero-trust network security", meeting_context="first_call". Add naics_code to surface expiring-contract questions.

输入模式

{
  "type": "object",
  "properties": {
    "agency": {
      "type": "string",
      "description": "Federal agency the meeting is with — name, acronym, or code, e.g. \"DHS\"."
    },
    "product_category": {
      "type": "string",
      "minLength": 3,
      "description": "What you sell, in plain words — e.g. \"data analytics platform\", \"zero-trust network security\"."
    },
    "naics_code": {
      "description": "Optional NAICS code for your category — adds questions about specific expiring contracts.",
      "type": "string",
      "pattern": "^\\d{2,6}$"
    },
    "meeting_context": {
      "default": "first_call",
      "description": "What kind of meeting you are prepping for.",
      "type": "string",
      "enum": [
        "first_call",
        "technical_deep_dive",
        "procurement_discussion"
      ]
    }
  },
  "required": [
    "agency",
    "product_category"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}
🟢qualify_opportunity(agency, product_category, estimated_value_usd, incumbent_vendor, deal_facts)

Use this to pressure-test a federal deal: pass what you know per MEDDPICC dimension (leave unknowns empty) and get back an evidence-scored scorecard adapted for public sector — budget authority instead of generic economic buyer, procurement vehicle as the paper process — with gap-closing questions and public-record evidence pulled automatically (name the incumbent_vendor and their real awards/end dates at the agency get attached). Scores measure evidence specificity, not truth; the response says what verified evidence looks like for each dimension.

输入模式

{
  "type": "object",
  "properties": {
    "agency": {
      "type": "string",
      "description": "Federal agency the deal is at — name, acronym, or code, e.g. \"DHS\"."
    },
    "product_category": {
      "type": "string",
      "minLength": 3,
      "description": "What you are selling, e.g. \"SIEM platform\"."
    },
    "estimated_value_usd": {
      "description": "Rough deal size in USD, if known.",
      "type": "number",
      "exclusiveMinimum": 0
    },
    "incumbent_vendor": {
      "description": "Competitor/incumbent vendor name if known — their real awards at this agency get pulled as evidence.",
      "type": "string"
    },
    "deal_facts": {
      "description": "What you know so far, one field per MEDDPICC dimension. Omit entirely (or leave fields empty) for pure-discovery scoring — gaps are the output.",
      "type": "object",
      "properties": {
        "metrics": {
          "description": "Quantified mission outcome the buyer expects (their numbers, not your pitch).",
          "type": "string"
        },
        "economic_buyer": {
          "description": "Who has budget/obligation authority — name, role, what they've said.",
          "type": "string"
        },
        "decision_criteria": {
          "description": "How they'll evaluate — technical factors, past performance, price weighting.",
          "type": "string"
        },
        "decision_process": {
          "description": "Steps and dates to award — RFI, evaluation, decision milestones.",
          "type": "string"
        },
        "paper_process": {
          "description": "Procurement path — vehicle, contract type, contracting office, ceiling.",
          "type": "string"
        },
        "identified_pain": {
          "description": "The forcing function — mandate, audit finding, incident, failed program.",
          "type": "string"
        },
        "champion": {
          "description": "Who sells for you internally — name, role, what they've done for you so far.",
          "type": "string"
        },
        "competition": {
          "description": "Who else is in — incumbent, other bidders, or internal do-nothing option.",
          "type": "string"
        }
      }
    }
  },
  "required": [
    "agency",
    "product_category"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

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最近观测

已验证未记录版本5 个工具
已验证未记录版本5 个工具
已验证未记录版本5 个工具