cap_table.delete_stakeholderDelete a selected planning stakeholder and associated records after exact confirmation at the current cap-table version.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | ||
| cap_table_id | Yes | ||
| stakeholder_id | Yes | ||
| idempotency_key | Yes | ||
| expected_version | Yes | ||
| confirmation_token | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint and idempotentHint, so the description is not required to repeat those. It adds meaningful behavior: deletion also removes 'associated records', requires 'exact confirmation', and is version-specific. This goes beyond the structured annotations without contradicting them.
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, well-structured sentence that front-loads the action and object and packs the key constraints (associated records, exact confirmation, current version) without filler or redundancy.
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?
While the output schema covers return values and annotations cover destructive/idempotent behavior, the tool still has six parameters with zero schema-level descriptions. The description only partially explains the confirmation and version parameters, leaving the agent unable to confidently construct all required arguments.
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 0%, so the description must compensate, but it only hints at expected_version and confirmation_token via 'current cap-table version' and 'exact confirmation'. The remaining parameters (project_id, cap_table_id, stakeholder_id, idempotency_key) have no semantic explanation anywhere, leaving the agent under-informed.
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 ('Delete') with a precise resource ('selected planning stakeholder') and scope ('associated records'), clearly distinguishing it from sibling tools like cap_table.delete, cap_table.create_stakeholder, and cap_table.update_stakeholder. The context 'at the current cap-table version' also adds needed specificity.
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 that this tool is used to delete a stakeholder for a cap table, but it never explicitly states when to prefer it over cap_table.delete or when not to use it. The usage context is inferable from the name and description, but no exclusions or alternative guidance are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Domain prefixes (crm., cap_table., landing.) clearly separate broad modules, and most tools target a specific resource and action. However, within modules there are boundary overlaps—crm.add_contact_note vs crm.log_activity and cap_table.dilution_preview vs cap_table.simulate_raise—where descriptions must be read carefully to avoid a wrong pick.
The dominant pattern is module.verb_noun (e.g., crm.create_lead, cap_table.update_stakeholder), which is clear and readable. But a subset of top-level tools uses object_verb with flat underscores (e.g., shortlink_create, qr_generate, campaign_archive) and one outlier (campaign_stats) breaks the verb pattern, so conventions are mixed.
86 tools is an extreme surface for any single MCP server, well past the 50+ threshold that makes coherent selection impractical. Even though the features span several business domains, this would be far more usable split into focused servers per module.
The covered domains are broadly complete: cap table, CRM, incorporation, landing, projects, sparkroom, tasks, and validation all have read/write workflows with few dead ends. Minor gaps remain (no campaign listing/update, no branding palette delete/update, no contact deletion) but none of them blocks the main product workflows.