Costory: Your Finops MCP

list_available_destinations

List Slack and Teams destinations available through the organization's configured integrations and the signed-in user's email when available. Use to select a destination for a report or alert. Slack discovery may open a DM with the signed-in user; it does not send a message. Returns an object keyed by provider — destinations.slack.channels[] (channelId, name), destinations.teams.channels[] (channelId, name, teamName), and destinations.email (free-form; no list to enumerate). Each provider also carries a "connected" boolean so you can tell the user when an integration isn't set up. Call this before create_report or create_alert to resolve channelId values. For email, destinations.email.self (when present) is the signed-in user's own address — use it for "email me" instead of asking; destinations.email also accepts the literal ALL_ACTIVE_USERS to reach every active user. For any other explicit recipient, ask the user for the address. EXAMPLE: "Send me a weekly digest to #infra-costs" → { } (then pick channels[].channelId where name === "infra-costs")

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "context": "<context>"
    },
    "name": "list_available_destinations"
  }
}

Input Schema

Name	Required	Description
`slug`	No	Organization slug. Omit to auto-detect from your account (fails if you belong to multiple orgs).
`context`	Yes	A few words on why you are calling this tool, for the server developer's analytics. Describe people and things by role, such as "a customer". Do not quote the user or include names, emails, or other personal details.
`llm_model`	No	The model identifier you are running as, for example "claude-opus-4-8" or "gpt-5.2". Pass "unknown" if you are not certain. Recorded for the server developer's analytics.
`conversation_id`	No	The conversation_id this server returned earlier in this conversation, unchanged, including after later user messages. Omit it if you have none. Recorded for the server developer's analytics.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 14, 2026

changedInput schema / properties / context / description

Previous value: -"Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""New value: +"A few words on why you are calling this tool, for the server developer's analytics. Describe people and things by role, such as \"a customer\". Do not quote the user or include names, emails, or other personal details."

changedInput schema / required

Previous value: -[
-  "context",
-  "llm_model"
-]New value: +[
+  "context"
+]

Changed4 schema fields changedNov 12, 2026

addedInput schema / properties / context

Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}

addedInput schema / properties / conversation_id

Added value: +{
+  "description": "The conversation_id this server returned earlier in this conversation, unchanged, including after later user messages. Omit it if you have none. Recorded for the server developer's analytics.",
+  "type": "string"
+}

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The model identifier you are running as, for example \"claude-opus-4-8\" or \"gpt-5.2\". Pass \"unknown\" if you are not certain. Recorded for the server developer's analytics.",
+  "type": "string"
+}

addedInput schema / required

Added value: +[
+  "context",
+  "llm_model"
+]

First observedAug 19, 2026

TDQS

A4.6/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations say readOnlyHint=false, and the description explains exactly why: "Slack discovery may open a DM with the signed-in user; it does not send a message." That side effect plus the per-provider "connected" boolean and the warning that integrations may not be set up is precisely the behavioral context annotations alone cannot convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then return shape, then the call-ordering rule, then recipient rules — a logical progression with no filler. It is dense and long-ish, but nearly every clause carries an actionable detail, and the worked example is compact.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description carries the return-value burden and does so completely: it enumerates destinations.slack.channels[], destinations.teams.channels[] with teamName, and destinations.email with its free-form/ALL_ACTIVE_USERS semantics. An agent can call it and interpret the result without further documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so slug, context, llm_model, and conversation_id are already fully documented as analytics/metadata fields. The description adds no additional meaning about them, which is the expected baseline when the schema does the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific verb and resource set — "List Slack and Teams destinations available through the organization's configured integrations" — plus the user's email. It is clearly distinguishable from sibling list tools like list_teams and list_users because it scopes to report/alert delivery targets.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to call it ("Use to select a destination for a report or alert", "Call this before create_report or create_alert to resolve channelId values") and gives decision rules for edge cases: use destinations.email.self for "email me", ALL_ACTIVE_USERS for everyone, and ask the user for any other explicit recipient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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