Territory News MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Territory News MCP ServerPre-call battlecard for Datadog ahead of my 2pm meeting"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Territory News MCP Server π
Model Context Protocol (MCP) Server for Territory News β Real-time Account Intelligence, Deal Signals & Strategic Openers for Enterprise Sales & Account Executives.
π― Overview
Territory News MCP (tnews-mcp) frees Account Executives (AEs) and sales teams from being chained to the manual Territory News web UI. By exposing territory configuration, company search, real-time signal preview, and AI-enriched seller context over the open Model Context Protocol (MCP) standard, tnews-mcp allows autonomous orchestratorsβsuch as n8n, OpenClaw, Agentic Hermes, Claude Desktop, Cursor, Gemini, and custom Slack AI Agentsβto continuously execute high-leverage sales workflows in the background.
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["β 8:00 AM Morning Intelligence Briefing"]
LLM --> W2["β‘ 5-Minute Pre-Call Battlecard Generator"]
LLM --> W3["π― Trigger-Based Stalled Deal Reactivation"]
LLM --> W4["π₯ Multi-Threading Consensus Matrix"]
LLM --> W5["π Closed-Loop Feedback & Relevance Tuning"]Related MCP server: FundzWatch MCP Server
β‘ The 5 Autonomous Agent Workflows (Freeing You from the UI)
Instead of logging into territory.news every morning to manually click through accounts and copy openers, connect tnews-mcp to your multi-agent runner (n8n cron trigger, OpenClaw agent, or Hermes):
1. β 8:00 AM Morning Intelligence Briefing & Action Queue
How It Works: Every morning at 8:00 AM, an n8n / OpenClaw cron job awakens your sales agent.
Orchestration:
The agent calls CRM MCP to fetch your active pipeline (Stages 2β4) and top Tier-1 target accounts.
It invokes
territory_get_signalsontnews-mcpto scan for material catalysts over the last 24 hours (e.g., CapEx expansion, CIO hires, earnings surprises, restructuring).It cross-references your configured seller value proposition (
territory_get_seller_context) and synthesizes a 3-item Slack digest with 1-click pre-drafted outreach emails.
AE Impact: You wake up to prioritized, ready-to-send outreach in Slack rather than combing through Google Alerts or web tabs.
2. β‘ 5-Minute Pre-Call Battlecard Generator
How It Works: 10 minutes prior to any calendar event, your agent triggers automatically.
Orchestration:
Calendar MCP detects an upcoming meeting (e.g., "Discovery with VP of Engineering at Datadog").
Agent calls
territory_preview_signals(company="Datadog", domain="datadoghq.com")to pull breaking news and financial catalysts.Agent calls CRM MCP to fetch previous call objections and notes.
Agent delivers a 1-page tactical battlecard to your inbox or scratchpad containing:
Strategic Imperatives: What the account is currently navigating.
Persona Top-of-Mind: Key KPIs and friction points for the attendee's role.
3 Provocative Openers: POV-led conversation starters directly connecting their public news to your product.
Landmines: Competitor presence or sensitive topics to avoid.
3. π― Trigger-Based Stalled Deal Reactivation
How It Works: Re-engaging ghosted or closed-lost deals with authentic value instead of "just checking in".
Orchestration:
Agent queries CRM MCP for deals in Stalled / No Contact > 30 Days with ARR > $50k.
Agent queries
territory_get_signalsfor major inflection events (e.g., new executive hires, earnings beats, M&A, regulatory changes).When an event fires (e.g., "EquipmentShare Jumps on 26% Revenue Growth"), the agent drafts a contextual follow-up connecting the growth to solving the specific bottleneck documented in CRM notes.
4. π₯ Multi-Threading Consensus Matrix
How It Works: Enterprise deals require consensus across 6β10 stakeholders.
Orchestration:
When a single major catalyst is identified for a target account via
tnews-mcp, the agent automatically maps the event to distinct personas:To CFO: Cost containment, OPEX reduction, and vendor consolidation angles.
To CISO / Security: Compliance automation, zero-trust architecture, and audit risk reduction.
To VP Engineering: Developer velocity, eliminating deployment toil, and DORA metric acceleration.
The agent queues tailored outreach drafts in your email client via Email MCP.
5. π Closed-Loop Feedback & Relevance Tuning
How It Works: Continuous improvement of signal quality without manual configuration.
Orchestration:
When you accept, edit, or reject an outreach recommendation in Slack or Claude, the agent automatically invokes
territory_submit_feedbackontnews-mcp.This provides immediate closed-loop telemetry back to Territory News to tune signal scoring and relevance models for your territory over time.
ποΈ Architecture: Hybrid Browser Auth + Direct REST API
This MCP server uses a high-performance hybrid architecture:
One-Time Browser Login: Launches a visible browser window once to sign in via Clerk (Work Email / Google SSO). It automatically captures the session token and saves it locally to
~/.territory-mcp/session.json.100% Direct REST API: All subsequent operations run via lightning-fast HTTP REST requests directly against Territory News endpoints (
< 150mslatency, zero browser overhead, completely immune to DOM/UI changes).
π Quickstart
1. Installation
# Clone the repository
git clone https://github.com/junoonx/tnews-mcp.git
cd tnews-mcp
# Install dependencies and build
npm install
npm run build2. Connect to Your AI Host / Orchestrator
A. Claude Desktop
Add this to your claude_desktop_config.json (located at ~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows):
{
"mcpServers": {
"territory-news": {
"command": "node",
"args": ["/absolute/path/to/tnews-mcp/dist/index.js"]
}
}
}B. Cursor IDE / Cline / Windsurf
Add to your .cursor/mcp.json or MCP settings:
{
"mcpServers": {
"territory-news": {
"command": "node",
"args": ["/absolute/path/to/tnews-mcp/dist/index.js"]
}
}
}C. n8n / OpenClaw / Agentic Hermes / Docker
Pass the stdio command or set TERRITORY_SESSION_TOKEN in your environment:
TERRITORY_SESSION_TOKEN="your_clerk_session_jwt" node dist/index.jsπ Authentication
Method 1: Interactive Browser Login (Recommended)
Ask your AI assistant in Claude/Cursor:
"Log in to Territory News"
The server will invoke territory_login_browser, opening a browser window to territory.news. Log in with your work email or SSO. The browser will automatically save your session to ~/.territory-mcp/session.json and close itself.
Alternatively, you can run it directly from your terminal:
npm run loginMethod 2: Headless Environment Variable
You can provide your session token directly:
export TERRITORY_SESSION_TOKEN="your_clerk_session_jwt_or_cookie"π οΈ MCP Tools Reference
Tool Name | Parameters | Description |
| (none) | Check authentication state, user email, and tracked accounts count. |
|
| Opens visible browser window for one-time Clerk sign-in. |
| (none) | Clears saved session credentials from local storage. |
|
| Search public/private companies with fuzzy name matching. |
|
| Preview qualified real-time signals/headlines for any company. |
| (none) | List all currently monitored companies in your territory (1β10 accounts). |
|
| Add, remove, or replace accounts in your monitored territory. |
| (none) | View your active seller persona, role, product, and value proposition. |
|
| Configure sales context & trigger AI context enrichment. |
|
| Fetch real-time signals, strategic POVs, and deal openers for territory accounts. |
| (none) | Triggers a live re-scan of news and deal triggers across all territory accounts. |
|
| Submit feedback to improve signal relevance and AI deal openers. |
π‘ Example Prompts to Try with Your Agent
1. Pre-Call Discovery Battlecard
"I have a 2:00 PM discovery call with Datadog. Check my Territory News signals for Datadog, map them to my seller context, and give me a 1-page pre-call battlecard with 3 high-impact conversation openers."
2. Territory Account Setup
"Search for Snowflake, Datadog, Stripe, and HashiCorp on Territory News and add them to my monitored territory."
3. Seller Profile Alignment
"Update my Territory News seller context: I am an Enterprise AE selling an AI observability & FinOps platform. My primary use case is reducing cloud migration risk and Kubernetes egress waste. My value proposition is: 'We help enterprise platform teams prevent unexpected multi-cloud egress spikes and optimize compute utilization without manual SRE tuning.'"
4. Monday Morning Deal Trigger Briefing
"Run a scan on all my Territory accounts. Show me the top 3 high-leverage inflection events (earnings, leadership changes, product shifts) and draft a 1-click personalized email for each."
π License
MIT License. Built for high-performing sellers and modern sales engineering teams.
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 freshnessβleaving 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 verbβresource 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. Dates show when Glama detected each change.
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
Every tool has a clearly distinct purpose: authentication, company search, signal preview, tracking management, seller context, signal retrieval, scan triggering, and feedback. No overlapping or ambiguous tools.
All tools follow the identical pattern of 'territory_' prefix followed by verb_noun (e.g., search_companies, get_signals, set_seller_context). Perfectly consistent naming convention.
12 tools is well within the ideal 3-15 range and each tool serves a necessary function for the territory news monitoring workflow. No bloat or missing essential operations.
The tool surface covers the full lifecycle: authentication, company discovery and tracking, seller context configuration, signal retrieval and scanning, and feedback. No obvious gaps for the stated purpose.
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