Territory News MCP Server
Territory News MCP Server 🚀
Territory News를 위한 Model Context Protocol(MCP) 서버 — 엔터프라이즈 영업 및 AE(Account Executive)를 위한 실시간 계정 인텔리전스, 딜 시그널, 전략적 오프너.
🎯 개요
**Territory News MCP(tnews-mcp)**는 AE(Account Executive)와 영업 팀이 수동으로 작업해야 하는 Territory News 웹 UI에 얽매이지 않도록 해방합니다. 오픈 Model Context Protocol(MCP) 표준을 통해 영역 구성, 기업 검색, 실시간 시그널 미리보기, AI 강화 셀러 컨텍스트를 제공함으로써 tnews-mcp는 n8n, OpenClaw, Agentic Hermes, Claude Desktop, Cursor, Gemini, 맞춤형 Slack AI 에이전트와 같은 자율 오케스트레이터가 백그라운드에서 영향력 높은 영업 워크플로를 지속적으로 실행할 수 있게 합니다.
graph TD
subgraph "MCP Ecosystem"
Cal_MCP["Calendar MCP<br/>(Google / Outlook)"]
T_MCP["Territory News MCP<br/>(Signals, POV, Openers, Tracking)"]
C_MCP["CRM MCP<br/>(Salesforce / HubSpot)"]
E_MCP["Email MCP<br/>(Gmail / Outlook)"]
end
subgraph "Autonomous Orchestration Layer (n8n / OpenClaw / Hermes Agent / Claude)"
LLM["LLM Reasoning & Strategy Engine<br/>(Claude / Gemini / Llama / Hermes)"]
end
Cal_MCP -->|"Upcoming Meetings & Attendees"| LLM
T_MCP -->|"Account News, Executive Moves, Triggers"| LLM
C_MCP -->|"Pipeline Stages, Account Tier, Notes"| LLM
E_MCP -->|"Outreach Drafts & Sequences"| LLM
LLM --> W1["☕ 8:00 AM Morning Intelligence Briefing"]
LLM --> W2["⚡ 5-Minute Pre-Call Battlecard Generator"]
LLM --> W3["🎯 Trigger-Based Stalled Deal Reactivation"]
LLM --> W4["👥 Multi-Threading Consensus Matrix"]
LLM --> W5["🔄 Closed-Loop Feedback & Relevance Tuning"]Related MCP server: DataLayer MCP
⚡ 5가지 자율 에이전트 워크플로(UI에서 해방)
매일 아침 territory.news에 로그인해서 계정을 수동으로 클릭하며 오프너를 복사하는 대신, tnews-mcp를 멀티 에이전트 러너(n8n cron 트리거, OpenClaw 에이전트 또는 Hermes)에 연결하세요:
1. ☕ 오전 8시 인텔리전스 브리핑 및 액션 큐
작동 방식: 매일 오전 8시에 n8n / OpenClaw cron 작업이 영업 에이전트를 깨웁니다.
오케스트레이션:
에이전트가 CRM MCP를 호출하여 활성 파이프라인(Stages 2–4)과 주요 Tier-1 타겟 계정을 가져옵니다.
tnews-mcp에서 **territory_get_signals**를 호출하여 지난 24시간 동안의 중요한 촉매(예: CapEx 확장, CIO 영입, 실적 서프라이즈, 구조조정)를 스캔합니다.설정된 셀러 가치 제안(
territory_get_seller_context)과 교차 참조하여 1클릭으로 바로 보낼 수 있는 사전 작성 아웃리치 이메일이 포함된 3개 항목 Slack 다이제스트를 생성합니다.
AE 영향: Google 알리미나 웹 탭을 일일이 뒤질 필요 없이 Slack에서 우선순위가 정해지고 바로 보낼 수 있는 아웃리치를 확인하며 하루를 시작합니다.
2. ⚡ 5분 프리콜 배틀카드 생성기
작동 방식: 캘린더 이벤트 10분 전에 에이전트가 자동으로 트리거됩니다.
오케스트레이션:
Calendar MCP가 다가오는 미팅(예: "Datadog의 엔지니어링 VP와 디스커버리 미팅")을 감지합니다.
에이전트가 **
territory_preview_signals(company="Datadog", domain="datadoghq.com")**를 호출하여 속보와 재무 촉매를 가져옵니다.에이전트가 CRM MCP를 호출하여 이전 통화의 오브젝션과 노트를 가져옵니다.
에이전트가 다음을 포함하는 1페이지 분량의 전술 배틀카드를 받은 편지함 또는 스크래치패드에 전달합니다:
전략적 핵심 과제: 해당 계정이 현재 직면하고 있는 핵심 현안.
페르소나 최우선 관심사: 참석자 역할에 대한 핵심 KPI와 마찰 지점.
도발적인 오프너 3가지: 그들의 공개 뉴스를 제품에 직접 연결하는 POV 기반 대화 시작 문구.
지뢰(피해야 할 사항): 피해야 할 경쟁사 존재 또는 민감한 주제.
3. 🎯 트리거 기반 정체된 딜 재활성화
작동 방식: 연락이 끊기거나 탈락(closed-lost)한 딜을 "그냥 안부 확인"이 아닌 진정한 가치로 다시 소통합니다.
오케스트레이션:
에이전트가 CRM MCP에서 ARR > $50k이고 정체됨 / 30일 이상 연락 없음 상태인 딜을 조회합니다.
에이전트가 **
territory_get_signals**를 조회하여 주요 변곡 이벤트(예: 신임 임원 영입, 실적 상회, M&A, 규제 변경)를 확인합니다.이벤트가 발생하면(예: "EquipmentShare, 26% 매출 성장에 급등") 에이전트가 CRM 노트에 기록된 특정 병목 해결과 이 성장을 연결하는 맥락 있는 후속 메시지를 작성합니다.
4. 👥 멀티스레딩 합의 매트릭스
작동 방식: 엔터프라이즈 딜은 6~10명의 이해관계자 간 합의가 필요합니다.
오케스트레이션:
tnews-mcp를 통해 타겟 계정에서 단일 주요 촉매가 식별되면 에이전트가 이벤트를 서로 다른 페르소나에 자동으로 매핑합니다:CFO에게: 비용 통제, OPEX 절감, 벤더 통합 관점.
CISO / 보안 담당자에게: 규정 준수 자동화, 제로 트러스트 아키텍처, 감사 위험 감소.
엔지니어링 VP에게: 개발자 생산성, 배포 토일 제거, DORA 지표 가속화.
에이전트가 Email MCP를 통해 맞춤형 아웃리치 초안을 이메일 클라이언트에 대기열로 추가합니다.
5. 🔄 폐쇄 루프 피드백 및 관련성 튜닝
작동 방식: 수동 구성 없이 시그널 품질을 지속적으로 개선합니다.
오케스트레이션:
Slack이나 Claude에서 아웃리치 추천을 수락, 수정 또는 거부하면 에이전트가
tnews-mcp에서 **territory_submit_feedback**를 자동으로 호출합니다.이를 통해 Territory News에 즉각적인 폐쇄 루프 텔레메트리가 전달되어 시간이 지남에 따라 내 영역에 대한 시그널 점수 산정과 관련성 모델을 조정할 수 있습니다.
🏗️ 아키텍처: 하이브리드 브라우저 인증 + 직접 REST API
이 MCP 서버는 고성능 하이브리드 아키텍처를 사용합니다:
일회성 브라우저 로그인: Clerk(회사 이메일 / Google SSO)을 통해 로그인하도록 브라우저 창을 한 번 엽니다. 세션 토큰을 자동으로 캡처하여
~/.territory-mcp/session.json에 로컬로 저장합니다.100% 직접 REST API: 이후의 모든 작업은 Territory News 엔드포인트에 대한 초고속 HTTP REST 요청을 통해 직접 실행됩니다(
< 150ms지연 시간, 브라우저 오버헤드 없음, DOM/UI 변경에 완전히 영향받지 않음).
🚀 빠른 시작
1. 설치
# Clone the repository
git clone https://github.com/junoonx/tnews-mcp.git
cd tnews-mcp
# Install dependencies and build
npm install
npm run build2. AI 호스트 / 오케스트레이터에 연결
A. Claude Desktop
이 내용을 claude_desktop_config.json에 추가하세요(macOS에서는 ~/Library/Application Support/Claude/claude_desktop_config.json, Windows에서는 %APPDATA%\Claude\claude_desktop_config.json에 있습니다):
{
"mcpServers": {
"territory-news": {
"command": "node",
"args": ["/absolute/path/to/tnews-mcp/dist/index.js"]
}
}
}B. Cursor IDE / Cline / Windsurf
.cursor/mcp.json 또는 MCP 설정에 추가하세요:
{
"mcpServers": {
"territory-news": {
"command": "node",
"args": ["/absolute/path/to/tnews-mcp/dist/index.js"]
}
}
}C. n8n / OpenClaw / Agentic Hermes / Docker
stdio 명령을 전달하거나 환경에 TERRITORY_SESSION_TOKEN을 설정하세요:
TERRITORY_SESSION_TOKEN="your_clerk_session_jwt" node dist/index.js🔐 인증
방법 1: 대화형 브라우저 로그인(권장)
Claude/Cursor에서 AI 어시스턴트에게 요청하세요:
"Territory News에 로그인해 주세요"
서버가 territory_login_browser를 호출하여 territory.news로 브라우저 창을 엽니다. 회사 이메일 또는 SSO로 로그인하세요. 브라우저가 세션을 ~/.territory-mcp/session.json에 자동으로 저장하고 스스로 닫힙니다.
또는 터미널에서 직접 실행할 수도 있습니다:
npm run login방법 2: 헤드리스 환경 변수
세션 토큰을 직접 제공할 수 있습니다:
export TERRITORY_SESSION_TOKEN="your_clerk_session_jwt_or_cookie"🛠️ MCP 도구 참조
도구 이름 | 매개변수 | 설명 |
| (없음) | 인증 상태, 사용자 이메일, 추적 중인 계정 수를 확인합니다. |
|
| 일회성 Clerk 로그인을 위해 브라우저 창을 엽니다. |
| (없음) | 로컬 저장소에서 저장된 세션 자격 증명을 삭제합니다. |
|
| 퍼지 이름 매칭으로 공개/비공개 기업을 검색합니다. |
|
| 모든 기업에 대해 검증된 실시간 시그널/헤드라인을 미리 봅니다. |
| (없음) | 내 영역에서 현재 모니터링 중인 모든 기업(1~10개 계정)을 나열합니다. |
|
| 모니터링 중인 영역의 계정을 추가, 제거 또는 교체합니다. |
| (없음) | 활성 셀러 페르소나, 역할, 제품 및 가치 제안을 확인합니다. |
|
| 영업 컨텍스트를 구성하고 AI 컨텍스트 강화를 트리거합니다. |
|
| 영역 계정에 대한 실시간 시그널, 전략적 POV, 딜 오프너를 가져옵니다. |
| (없음) | 모든 영역 계정에서 뉴스 및 딜 트리거에 대한 라이브 재스캔을 트리거합니다. |
|
| 시그널 관련성과 AI 딜 오프너를 개선하기 위해 피드백을 제출합니다. |
💡 에이전트와 함께 시도할 예시 프롬프트
1. 프리콜 디스커버리 배틀카드
"오후 2시에 Datadog와 디스커버리 콜이 있습니다. Territory News에서 Datadog 관련 시그널을 확인하고, 제 셀러 컨텍스트에 매핑한 후, 영향력 높은 대화 오프너 3개가 포함된 1페이지 프리콜 배틀카드를 주세요."
2. 영역 계정 설정
"Territory News에서 Snowflake, Datadog, Stripe, HashiCorp를 검색하여 모니터링 영역에 추가해 주세요."
3. 셀러 프로필 정렬
"내 Territory News 셀러 컨텍스트를 업데이트해 주세요: 저는 AI 옵저버빌리티 및 FinOps 플랫폼을 판매하는 엔터프라이즈 AE입니다. 주요 사용 사례는 클라우드 마이그레이션 위험과 Kubernetes 이그레스 낭비를 줄이는 것입니다. 제 가치 제안은 다음과 같습니다: '우리는 엔터프라이즈 플랫폼 팀이 수동 SRE 튜닝 없이 예상치 못한 멀티클라우드 이그레스 급증을 방지하고 컴퓨팅 활용도를 최적화할 수 있도록 돕습니다.'"
4. 월요일 아침 딜 트리거 브리핑
"내 모든 Territory 계정을 스캔하세요. 상위 3개의 고효율 변곡 이벤트(실적, 리더십 변경, 제품 변화)를 보여주고 각각에 대해 1클릭 개인화 이메일을 작성해 주세요."
📄 라이선스
MIT 라이선스. 고성과 셀러와 현대적인 세일즈 엔지니어링 팀을 위해 만들어졌습니다.
Available Tools
12 toolsterritory_auth_statusA
Check current authentication status for Territory News, including logged-in user email, user ID, and session file path.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It implies a read-only status check ('Check current authentication status') rather than a mutation, which is the key behavioral disclosure. It names specific fields returned, which is useful context. However, it does not explicitly say whether this performs any network/session mutation or what happens if no session exists.
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?
One efficient sentence, front-loaded with verb 'check' and resource 'authentication status'. The list of returned values is compact, though it could be slightly tighter.
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?
Simple zero-param read tool. The description identifies the checked resource and the three output facetscing. Could add a sentence on when to use it vs. the login and logout siblings, or clarify the meaning of the returned status.
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?
Zero parameters means the schema is trivially complete at 100% coverage. The description adds value by stating what the tool reports (user email, user ID, session file path), which goes beyond the empty schema.
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?
States a specific verb (check) + resource (Territory News) and enumerates the exact information returned: user email, user ID, and session file path. This clearly distinguishes it from the sibling auth tools territory_login_browser and territory_logout, which are action tools, not status tools.
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?
The tool's purpose implies it should be used to verify whether a session exists before login or after logout, but the description doesn't explicitly say this. It doesn't name territories_login_browser as the alternative for establishing a session. The context is clear but the exclusions and when-not guidance are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_get_seller_contextA
Get the seller's active sales context (Role, Account Segment, Selling Product, Primary/Secondary Use Cases, Value Proposition, and Enriched AI Context).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only operation but does not mention authentication requirements, despite sibling tools like territory_auth_status and territory_login_browser suggesting such a dependency. It lists return fields but offers no details on side effects, errors, or prerequisites.
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 front-loads the action and resource, followed by a parenthetical list of included fields. Every word earns its place, and the structure is clean and readable.
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?
For a parameterless getter, the description clearly indicates what is returned. However, it omits any mention of prerequisites like login or authentication, which could be critical given the sibling auth and login tools. Minor gap, but otherwise complete for its simplicity.
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?
The tool has zero parameters, so there is nothing to describe beyond what the empty schema shows. The description adds no parameter-related information, which is acceptable given the absence of parameters; a baseline of 4 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 ('Get') and resource ('seller's active sales context'), and lists specific components (Role, Account Segment, etc.). It is easily distinguished from the sibling setter 'territory_set_seller_context', which performs the opposite operation.
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?
The description does not explicitly state when to use this tool versus alternatives, such as the setter. While the getter nature implies use when you need the current context, there is no direct guidance on when to retrieve versus set, and no mention of prerequisites or common workflows.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_get_signalsB
Get real-time news signals, executive inflection events, and tailored conversation openers for all tracked accounts in your territory (or for specific requested companies).
| Name | Required | Description | Default |
|---|---|---|---|
| company | No | Optional: Filter signals to a specific company in your territory (e.g. 'Snowflake') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden of behavioral disclosure, but it only lists the types of content returned. It does not state whether the tool is read-only, whether it requires existing tracked accounts, whether any scanning is triggered, or how the 'real-time' claim relates to data freshness—leaving important agent-facing behaviors undocumented.
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 front-loaded sentence that names the returned resource types and the optional scope without any wasted words. It is appropriately sized and communicates the core purpose quickly.
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?
For a tool with one optional parameter and no required params, the description is reasonably complete, but with no output schema it should say more about the shape and granularity of the returned signals and events. It also leaves the relationship to tracked accounts and sibling signal-related tools unstated, which is a noticeable gap for an autonomous agent.
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?
The schema already fully documents the single optional 'company' parameter, so the description adds little beyond restating the filter concept. Schema description coverage is 100%, so the baseline of 3 applies; the phrase 'specific requested companies' reinforces flexibility but does not add semantics about value format or behavior.
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 uses a specific verb ('Get') and identifies precise resources: real-time news signals, executive inflection events, and tailored conversation openers, scoped to tracked accounts or an optional requested company. It is clearbut does not explicitly differentiate itself from the similar sibling 'territory_preview_signals', so some sibling-routing burden remains on the agent.
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?
There is no explicit guidance about when to use this tool versus alternatives such as 'territory_preview_signals' or 'territory_trigger_scan'. The optional company filter gives scope context, but the description lacks conditions, exclusions, or reference to sibling tools that would help an agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_get_tracked_companiesA
Get the list of currently monitored companies in your territory (supports up to 10 accounts).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It describes a 'get' operation, implying read-only behavior, but does not explicitly state side effects, permissions, or response format. It is adequate for a simple getter but lacks detail.
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 conveys the tool's purpose and a key constraint. No extraneous information or wordiness.
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?
Given the simplicity (no parameters, no output schema), the description provides sufficient context: it returns a list of currently monitored companies within a territory, and notes a limit. While it doesn't specify the exact data structure, it gives enough for basic usage.
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?
The tool has no parameters, so schema coverage is 100%. The description adds no parameter information because there are none, aligning with the baseline score for high schema coverage.
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 it retrieves the list of currently monitored companies in the user's territory, with a specific verb 'Get' and resource. It distinguishes from sibling tools like territory_search_companies or territory_update_tracked_companies, which have different purposes.
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?
The description mentions a limitation (supports up to 10 accounts) but does not explicitly state when to use this tool versus alternatives, nor does it provide when-not-to-use guidance. It is implied as the primary getter, but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_login_browserA
Launches a visible browser window for one-time Clerk authentication to Territory News. Captures the session cookie and saves it locally.
| Name | Required | Description | Default |
|---|---|---|---|
| timeoutSeconds | No | Max seconds to wait for user to sign in in the browser (default: 180s) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full responsibility for behavioral disclosure. It mentions a 'visible browser window' (user interaction required), 'one-time' authentication, and that it captures and saves a session cookie. It does not specify what happens on failure or whether it overwrites an existing session, but the core behavior is well disclosed.
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 succinct sentence that conveys the key points without fluff. It covers the action, the target, the mechanism, and the outcome in a compact form.
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?
For an authentication tool with no annotationslogging, the description provides good context: it tells the agent that user interaction is required (visible browser), it captures a session cookie, and it has a timeout. It lacks information about return values or failure modes, but these may be less critical for a this kind of tool. Overall, it is fairly complete.
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?
The only parameter, timeoutSeconds, is fully described in the schema with its default value (180s). The description reinforces its purpose by saying 'Max seconds to wait for user to sign in.' There is no ambiguity.
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 ('Launches a visible browser window'), the specific resource ('Territory News'), and the outcome ('Captures the session cookie and saves it locally'). It is distinct from sibling tools like territory_auth_status (checking status) and territory_logout (ending session), making the purpose unambiguous.
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?
It describes the tool as 'one-time authentication' which gives context, but it does not explicitly state when to use this versus alternatives, nor does it mention prerequisites like needing to check auth status first. The guidance is implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_logoutA
Clear saved session credentials from local storage.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It explicitly discloses that the operation removes saved session credentials from local storage, which signals a destructive local side effect. It does not mention whether server-side sessions are invalidated or whether the call is safe when already logged out, but the core side effect is clear.
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?
Single sentence, no filler, front-loaded with the action. Every word earns its place.
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?
For a zero-parameter logout tool, the description states the essential effect. It lacks explicit usage context and any mention of return behavior, but the simplicity of the operation keeps the gap minor.
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?
The tool takes zero parameters, so the description cannot add parameter-level meaning. Baseline 4 applies because there is no schema information to compensate for.
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 uses a specific verb ('Clear') and resource ('saved session credentials from local storage'), clearly identifying it as the logout counterpart to territory_login_browser and territory_auth_status. It is not a tautology and conveys the exact operation.
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 guidance is given about when to call this tool versus territory_auth_status or territory_login_browser. An agent must infer that logout is appropriate after a session is no longer needed; there are no explicit conditions, prerequisites, or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_preview_signalsA
Preview recent real-time qualified news signals and headlines for a given company before adding it to your territory.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | Optional company domain (e.g. 'snowflake.com', 'anthropic.com') | |
| company | Yes | Company name (e.g. 'Snowflake', 'Anthropic') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The word 'Preview' implies a read-only, non-committal operation, which is useful behavioral context. However, it does not state whether authentication is required, whether any state changes occur, or how real-time data fetching behaves.
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 sentence with a front-loaded verb and resource. It contains no filler, no repetition of schema details, and every word contributes meaning.
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?
For a simple two-parameter preview tool, the schema covers the inputs completely. But with no output schema, the description could say more about what the returned signals/headlines look like and whether a login is a prerequisite; still, the core usage is understandable.
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?
Schema description coverage is 100%, so both parameters are already documented. The description only says 'given company' and adds no additional semantic detail beyond the schema, so the baseline score 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 opens with a specific verb ('Preview'), names the resource ('qualified news signals and headlines'), and scopes the use case ('before adding it to your territory'). This timing clearly distinguishes it from post-add signal retrieval like territory_get_signals, even without naming that sibling explicitly.
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?
The phrase 'before adding it to your territory' tells the agent exactly where this tool fits in the workflow. However, it does not explicitly state when not to use it or mention alternatives such as territory_get_signals for already-tracked companies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_search_companiesB
Search for public and private companies on Territory News using fuzzy name matching. Returns name, domain, logo, and ticker.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return (default: 8) | |
| query | Yes | Company name or search query (e.g. 'Snowflake', 'Datadog', 'Stripe') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses fuzzy matching and the return fields, which is useful. However, it doesn't mention whether this is a read-only operation, any rate limits, or what happens if no matches are found. For a search tool, this is adequate but not rich.
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 sentence that front-loads the purpose and includes the key return fields. It's concise with no waste, though it could mention the limit parameter's default behavior, which is already in the schema.
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?
For a search tool with a simple schema and no output schema, the description covers the essentials: what it searches, how (fuzzy), and what it returns. It lacks guidance on edge cases like empty results or pagination, but given the simplicity, it's reasonably complete.
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?
Schema description coverage is 100%, so both parameters are already documented. The description adds the context of fuzzy matching and return fields, but doesn't add syntax or format details beyond the schema. Baseline 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 tool searches for companies on Territory News with fuzzy name matching and returns specific fields. It distinguishes itself from siblings like territory_get_tracked_companies by focusing on search rather than tracking, though it doesn't explicitly name alternatives.
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?
The description implies usage for finding companies by name, but doesn't explicitly state when to use this vs. other tools like territory_get_tracked_companies or territory_get_seller_context. It provides no exclusions or alternative routing, leaving the agent to infer from the tool name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_set_seller_contextA
Configure or update your sales context (Role, Target Segment, Product Sold, Use Cases, Value Created). Automatically calls Territory News AI enrichment engine to tailor deal signals and conversation starters.
| Name | Required | Description | Default |
|---|---|---|---|
| role | No | Your sales role (e.g. 'AE') | |
| persona | No | Target account segment | |
| valueCreated | Yes | Detailed value proposition / pain relieved (min 60 chars recommended for optimal signal matching) | |
| primaryUseCase | Yes | Primary problem solved (e.g. 'Eliminate cloud compliance drift and accelerate SOC 2 audits') | |
| sellingProduct | Yes | What you sell (e.g. 'Enterprise Cloud Security & Observability platform') | |
| secondaryUseCases | No | Optional secondary use cases |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions that it automatically calls the 'Territory News AI enrichment engine', which is a behavioral trait, but does not disclose side effects (e.g., persistent mutation), permissions required, or error conditions. This is 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, concise and well-structured. The primary action is stated upfront, and the additional detail about the enrichment engine is relevant. No unnecessary verbosity.
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?
Given no output schema and no annotations, the description should clarify return values and prerequisites, but it does not. It explains what the tool does and its effect, but omits details about what the caller receives (e.g., success confirmation, errors) or any input requirements beyond the parameters.
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?
The schema has 100% description coverage, so the baseline is 3. The description summarizes the parameters (Role, Target Segment, etc.) but adds no new semantic information beyond what the parameter descriptions already provide.
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 tool's function: configuring or updating sales context. It also mentions the specific elements (role, target segment, etc.) and the effect (tailoring deal signals). This is specific and unambiguous.
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?
The description implies usage for setting or updating context, but does not explicitly contrast with the sibling tool 'territory_get_seller_context'. It does not state when to use this over alternatives, leaving some ambiguity for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_submit_feedbackA
Submit feedback on a signal, recommendation, or conversation starter to improve intelligence relevance.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | Feedback text (min 10 characters) | |
| feedbackType | Yes | Category of feedback | |
| sectionLabel | No | Optional specific signal title or UI section the feedback refers to |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Submit' implies a write operation, but the description does not state whether authentication is required, whether submission is idempotent, what side effects occur, or what response the agent should expect after a successful or failed submission.
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, front-loaded sentence with no filler. It names the action, the targets, and the purpose efficiently, and every phrase contributes to the agent's understanding.
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 tool is simple and its parameter schema is fully self-documenting, but there are no annotations and no output schema. The description omits behavioral context such as authentication requirements and expected response behavior, which an agent would need to handle the call gracefully. It is minimally viable but not fully complete.
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?
Schema description coverage is 100%, so the input schema already documents all three parameters, including the enum values and the minimum message length. The description adds little parameter-specific meaning beyond clarifying the domain objects the feedback refers to, which matches the baseline of 3.
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 states a specific action ('submit feedback') and identifies the exact targets: signals, recommendations, or conversation starters. It also indicates the intended outcome (improve intelligence relevance), which distinguishes it clearly from the sibling tools that search, preview, or manage tracked companies.
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?
The description provides clear context for when to use the tool: when a user wants to provide feedback on a signal, recommendation, or conversation starter. It does not explicitly name alternatives or state exclusions, but no sibling tool appears to serve a similar feedback purpose, so the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_trigger_scanB
Triggers a live re-scan of news and signal triggers across all monitored accounts in your territory.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It discloses 'triggers a live re-scan' but gives no details about whether the call blocks, what it returns, whether re-scan is asynchronous, or whether repeated triggers have side effects. This is a notable gap for an action that starts background work.
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, efficient sentence that front-loads the core action of 'Triggers a live re-scan' and includes the full scope without wasted words. It is appropriately concise, even it does not fully explore edge cases or behavior.
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?
Given that there is no output schema and no annotations, the description needed to explain return behavior and side effects, and it doesn't. An agent knows what the tool does, but cannot predict what a successful call returns or whether the operation is asynchronous or potentially destructive, leaving the description incomplete for this context.
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?
The input schema is an empty object with zero parameters, so the schema already fully documents the parameter space. The description adds no parameter details because none are needed, matching the 0-parameter baseline.
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 uses a specific verb–resource pairing: it 'triggers a live re-scan' of news and signal triggers across monitored accounts. This conveys a distinct, non-read-only purpose that differentiates it from related tools like territory_get_signals, though it does not explicitly name alternatives.
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?
The phrase 'across all monitored accounts in your territory' tells the agent the operational scope, but nothing explicitly states when this tool should be preferred over related alternatives such as territory_get_signals or territory_preview_signals. The intended usage is implied rather than clearly prescribed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
territory_update_tracked_companiesA
Add, remove, or replace monitored companies in your territory (max 10 companies). Automatically resolves domains and tickers.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | 'add' to append new companies, 'remove' to delete specific companies, or 'set' to replace the whole list. | |
| companies | Yes | List of company names or domains (e.g. ['Snowflake', 'datadoghq.com', 'Stripe']) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It does add useful behavioral facts beyond the schema: the 10-company cap and automatic domain/ticker resolution. However, it leaves unstated what happens on exceeding the cap, whether an authenticated territory session is required, and what the response looks like.
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 one tight sentence that front-loads the core operation and the most important constraint, then adds a valuable automatic-resolution note. No filler or repetition.
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?
For a two-parameter tool with a complete schema, the description covers the essential operational context: what actions are possible, the size limit, and input handling. It does not mention authentication/session requirements or failure modes, but the tool is simple enough that the remaining gaps are minor.
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?
The schema already describes both parameters fully (100% coverage), so the baseline is 3. The description adds meaningful semantics on top: it clarifies the 10-company limit for the companies array and explains that domain and ticker inputs are automatically resolved, which is not stated in the schema.
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 names a specific verb (add/remove/replace) and a specific resource (monitored companies in your territory), plus a key constraint (max 10). This clearly differentiates it from sibling read/search tools like territory_get_tracked_companies and territory_search_companies.
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?
The description makes it clear this tool is for modifying the monitored-company list, while the sibling names indicate read/search alternatives. It doesn't explicitly state 'use X instead when...', so it stops short of a full 5, but the intended usage is clear.
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.
12 tool updates
v1.0.0- First observed
territory_auth_status - First observed
territory_get_seller_context - First observed
territory_get_signals - First observed
territory_get_tracked_companies - First observed
territory_login_browser - First observed
territory_logout - First observed
territory_preview_signals - First observed
territory_search_companies - First observed
territory_set_seller_context - First observed
territory_submit_feedback - First observed
territory_trigger_scan - First observed
territory_update_tracked_companies
TDQS
Scored across 12 tools
Most tools map to distinct resources and actions: auth lifecycle, company search, tracked-company management, seller context, and signal retrieval are clearly separated. There is minor overlap between preview_signals and get_signals since get_signals can also target specific companies, though the intended pre-add versus tracked-account use case helps.
All tools share a consistent territory_ prefix and nearly all follow a verb_noun structure such as search_companies, get_tracked_companies, and set_seller_context. Small deviations like territory_auth_status and territory_login_browser weaken the verb-first pattern slightly, but the overall convention remains predictable.
12 tools is a well-scoped size for a territory intelligence MCP server, with separate groups for auth, company lookup, territory management, seller context, signals, and feedback. Each tool has a distinct responsibility and none feel redundant.
The surface covers the full workflow: authentication, company discovery, signal preview before adding, tracked-company management, seller context configuration, signal retrieval, live rescans, and feedback submission. There are no obvious dead ends or missing lifecycle operations.
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