The GVRN Incorporation MCP is a public Model Context Protocol (MCP) server that lets AI agents — on any LLM provider — collect and submit company incorporation requests to GVRN on a user's behalf.
Every submission is reviewed by GVRN's corporate secretarial team, who follow up with the user by email. All fields are optional, so an agent can submit early with whatever the user has provided and let a specialist fill in the gaps.
Creates a new incorporation request draft bound to the verified email, using any fields provided. Requires a verificationToken from verify_email_otp; every other field is optional. Returns a draftId that identifies the draft for later updates, submission, and status checks.
| Name | Required | Description | Default |
|---|---|---|---|
| notes | No | Anything else relevant: existing structures, PEP status, special requests | |
| urgency | No | Timeline constraints, e.g. "needed before token launch July 1" | |
| currency | No | Share capital currency, e.g. "USD" | |
| founders | No | Founders / shareholders / directors | |
| parValue | No | Par value per share | |
| entityType | No | e.g. "LTD", "FOUNDATION", "LLC" — free text is accepted | |
| companyName | No | Preferred company name | |
| totalShares | No | Total shares to be issued | |
| jurisdiction | No | Target jurisdiction, e.g. "BVI", "CAYMAN", "PANAMA" — free text is accepted | |
| verificationToken | Yes | Token from verify_email_otp — the draft is bound to this email | |
| businessDescription | No | What the company will do | |
| alternativeCompanyNames | No | Fallback company names in priority order |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations all false—no safety hints—the description carries the behavioral burden. It clearly states this is a create operation, that the draft is bound to the verified email token, that all fields except the token are optional, and that a draftId is returned for future steps. It does not discuss idempotency, error conditions, or token lifetime, but it discloses the core behavior and side effects well.
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?
Three tight sentences: the first states the core action and scope, the second gives the only prerequisite, and the third explains the return value's purpose. Nothing is redundant, and the most important information is front-loaded. Every sentence 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?
The tool has 12 parameters and no output schema, so the description must cover return behavior and the workflow context. It does: it identifies the required token, optionality, and the returned draftId for subsequent update/submission/status tools. It could be more complete by describing the exact response shape or failure modes, but for a draft-creation step the essentials are present.
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 schema fully documents each parameter. The description adds important meaning beyond the schema: verificationToken comes from verify_email_otp, every other field is optional, and the result is a reusable draftId. This contextual glue is more than a baseline schema-dependent description.
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 and resource: 'Creates a new incorporation request draft.' It further distinguishes this tool from siblings by emphasizing 'new' (vs update_incorporation_draft), 'draft' (vs submit_incorporation), and 'bound to the verified email' (vs verify_email_otp). An agent can clearly identify this as the creation step in the incorporation workflow.
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 gives clear usage context: it must be called after verify_email_otp because a verificationToken is required, and the returned draftId is used 'for later updates, submission, and status checks,' which maps to the sibling tools. It does not explicitly name an alternative or state when not to use it, but the flow is strongly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the full GVRN incorporation workflow guide: the fields collected, the email-verification steps, and the review lifecycle. Also available as the MCP resource gvrn://incorporation/guide.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and destructiveHint=false, so the safe read-only behavior is established. The description adds content scope and the alternative MCP resource URI, but discloses no further behavioral traits such as response format, pagination, or authentication requirements.
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?
Two compact, focused sentences. The primary return value is front-loaded, the content list adds concrete value, and the MCP resource note is delivered as a brief secondary detail.
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, read-only retrieval tool, the description is fully sufficient. It states what is returned, summarizes the guide's contents, and notes an alternative access method; no output schema is present but the description covers expectations adequately.
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 and the input schema is empty, so there is nothing for the description to clarify. With no 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?
States a specific verb and resource ('Returns the full GVRN incorporation workflow guide') and enumerates the content (fields, email-verification steps, review lifecycle). This clearly distinguishes it from the status, draft, and submission tools in the sibling list.
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 use when the full incorporation workflow guide is needed, but it gives no explicit when-to-use guidance and does not contrast with alternatives like get_incorporation_status or the draft/submit tools. The sibling list is not referenced within the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the current status of an incorporation request (DRAFT → QUEUED_FOR_REVIEW → UNDER_REVIEW → COMPLETED). Requires a verificationToken for the email that created the draft; requests are only visible to that email.
| Name | Required | Description | Default |
|---|---|---|---|
| draftId | Yes | Draft id returned by create_incorporation_draft | |
| verificationToken | Yes | Token from verify_email_otp |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds non-obvious behavioral traits: the token-to-email binding, per-email visibility (authorization filtering), and the lifecycle statuses. There is no contradiction with the annotations.
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?
Two sentences carry all essential information: the first states the result and status lifecycle, the second states the authentication and visibility constraint. No filler, no repetition of schema fields, and the core purpose is front-loaded.
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 read-only, two-parameter tool with annotations covering safety and no output schema, the description is sufficient: it names the returned status set and the ownership constraint. It could go slightly further by explicitly suggesting polling after submit_incorporation, but this is not necessary for correct invocation.
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% and both parameters reference their origin tools. The description adds meaning beyond the schema by explaining why verificationToken is required and how it scopes visibility ('for the email that created the draft; requests are only visible to that email'). This semantic context is not present 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 states a specific verb ('Returns') and a clear resource ('current status of an incorporation request'), and enumerates the exact status values (DRAFT → QUEUED_FOR_REVIEW → UNDER_REVIEW → COMPLETED). This distinguishes it from siblings like create_incorporation_draft or submit_incorporation, which clearly mutate or create state.
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 on prerequisites: a verificationToken tied to the email that created the draft, and the visibility constraint that requests are only visible to that email. It does not explicitly name alternative tools or say 'use this instead of X', but the workflow context is strongly implied through the schema references to create_incorporation_draft and verify_email_otp.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Sends a 6-digit verification code to the given email address. The code is exchanged for a verificationToken via verify_email_otp, and that token authorizes the draft tools. Codes expire after 10 minutes and are rate-limited per email.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Email address to verify — the user's real inbox |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate mutation (readOnlyHint=false) but non-destructive. The description adds that codes expire after 10 minutes and are rate-limited per email, which supplements the annotations without contradiction.
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?
Two sentences, no wasted words. Information is front-loaded: action, purpose, flow, constraints. Excellent efficiency.
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 one-parameter, no-output-schema tool, the description covers action, flow, expiration, rate-limiting, and integration with sibling tools. Entirely adequate.
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 has one parameter with full description coverage. The description adds the context 'the user's real inbox', reinforcing the email purpose meaningfully beyond 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 clearly states it sends a 6-digit code to an email and explains its role in the verification flow (exchanged for a token via verify_email_otp, authorizes draft tools). It distinguishes itself from the sibling tool verify_email_otp.
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 explicitly states the flow: send the code, then use verify_email_otp to exchange it. It provides clear context for when to use this tool (before verify_email_otp), though it doesn't explicitly mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Submits a draft for review by the GVRN team and returns the request status. Requires a verificationToken for the email that created the draft, which becomes the contact for the request. Optional fields may be left blank. Irreversible: the draft becomes read-only and a review request is filed with the GVRN team.
| Name | Required | Description | Default |
|---|---|---|---|
| draftId | Yes | Draft id returned by create_incorporation_draft | |
| verificationToken | Yes | Token from verify_email_otp |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly discloses irreversibility, that the draft becomes read-only, and that a review request is filed. This goes well beyond the destructiveHint=true annotation by saying exactly what state change happens and what the user should expect. It also clarifies the auth need for a verificationToken tied to the creating email.
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?
Four sentences with the core purpose front-loaded, then prerequisite and irreversibility. The sentence about optional fields being left blank is useful but somewhat tangential to the tool's own parameters, keeping it a half-step below perfect.
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 low-complexity tool with two well-described parameters and strong annotations, the description covers the submission outcome, auth requirement, irreversibility, and resulting state. The return value is simply described as the request status, which is sufficient given no output schema.
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 coverage is 100%, so the baseline is 3. The description adds meaning by clarifying that verificationToken must belong to the email that created the draft and that this email becomes the contact for the request, which is not fully 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 states a specific action: submitting a draft for review by the GVRN team, and says the tool returns the request status. This clearly distinguishes it from siblings like create_incorporation_draft, update_incorporation_draft, and get_incorporation_status.
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 gives clear context for when to call it: after a draft exists and the email has been verified, since a verificationToken is required. It does not explicitly name alternatives or say when not to use it, so it misses the full 'when-not/alternatives' framing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Adds or corrects fields on an existing draft (patch semantics: only provided fields are changed; array fields are replaced whole). Requires a verificationToken for the email that created the draft. Fails once the draft has been submitted.
| Name | Required | Description | Default |
|---|---|---|---|
| notes | No | Anything else relevant: existing structures, PEP status, special requests | |
| draftId | Yes | Draft id returned by create_incorporation_draft | |
| urgency | No | Timeline constraints, e.g. "needed before token launch July 1" | |
| currency | No | Share capital currency, e.g. "USD" | |
| founders | No | Founders / shareholders / directors | |
| parValue | No | Par value per share | |
| entityType | No | e.g. "LTD", "FOUNDATION", "LLC" — free text is accepted | |
| companyName | No | Preferred company name | |
| totalShares | No | Total shares to be issued | |
| jurisdiction | No | Target jurisdiction, e.g. "BVI", "CAYMAN", "PANAMA" — free text is accepted | |
| verificationToken | Yes | Token from verify_email_otp for the email that created the draft | |
| businessDescription | No | What the company will do | |
| alternativeCompanyNames | No | Fallback company names in priority order |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, the description discloses important behavior: patch semantics, array replacement behavior, verification token requirement, and failure after draft submission. This adds meaningful behavioral context that annotations alone do not provide.
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?
Three short sentences, each carrying essential information. The description is front-loaded with the core behavior and then covers requirements and constraints with no wasted words.
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 complex 13-parameter update tool, the description covers the key invocation concerns: operation type, patch semantics, required token, and lifecycle restriction. The schema handles parameter details, and no output schema is declared, so the description is sufficiently complete for correct invocation.
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 coverage is 100%, so parameters are already well-documented. The description adds valuable semantics explaining how parameters are applied: only provided fields are changed and array fields are replaced whole. This goes beyond the schema's field-level descriptions.
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 verb and resource: 'Adds or corrects fields on an existing draft.' It also clarifies patch semantics, which distinguishes it from create_incorporation_draft and submit_incorporation. This is clear and not tautological.
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 clearly implies when to use the tool: on an existing draft, before submission. It also states a hard prerequisite (verificationToken for the creating email) and a hard exclusion (fails after submission). It does not explicitly name sibling alternatives, but the context and failure condition provide adequate guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Verifies a 6-digit email code and returns a verificationToken valid for ~30 minutes. The draft tools require this token. Re-verifying the same email issues a fresh token that still reaches the same drafts.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | The 6-digit code from the user's inbox | |
| Yes | Same email the code was sent to |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds meaningful behavioral details beyond the annotations: the token is valid for ~30 minutes, re-verification issues a fresh token, and the fresh token still reaches the same drafts. It also implies a state-changing operation consistent with readOnlyHint=false, with no contradiction.
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?
Two sentences with no filler. The core action and output are front-loaded, and the token's role in the broader workflow is stated in the second sentence. Every sentence adds value.
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 verification tool with no output schema, the description covers the return value, token expiry, downstream dependency, and idempotency-like behavior. Nothing essential for correct invocation is missing.
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 coverage is 100%, and both 'email' and 'code' are already described accurately in the schema. The description's mention of a '6-digit code' matches rather than extends the schema. Since the schema carries the parameter meaning, a baseline score 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?
States a specific verb ('verifies'), a specific resource ('6-digit email code'), and the key output ('verificationToken'). It also distinguishes itself from the sibling request_email_otp by focusing on verification rather than sending. The title matches the function clearly.
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 explicitly says draft tools require this token, which tells the agent when this tool fits in the workflow. It does not explicitly name alternatives or exclusion conditions, but the token requirement provides clear contextual guidance and placement after receiving the email code.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
create_incorporation_draftget_incorporation_guideget_incorporation_statusrequest_email_otpsubmit_incorporationupdate_incorporation_draftverify_email_otpClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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Add one secure layer between your agents and this server.
Each tool maps to a distinct lifecycle step: OTP request/verify, draft create/update/submit, status, and guide retrieval. The only closely related pair, request_email_otp and verify_email_otp, is clearly separated by one sending a code and one exchanging it for a token.
All tool names follow a consistent verb_noun pattern in snake_case, such as create_incorporation_draft, update_incorporation_draft, and verify_email_otp. Minor variation like submit_incorporation instead of submit_incorporation_draft does not hurt predictability.
Seven tools is well-scoped for an incorporation workflow: email verification, draft management, submission, status checks, and a guide. Each tool has a clear purpose and none feel redundant.
The tool set covers the full applicant journey from guide and email verification through draft creation, editing, submission, and status tracking. There is no delete/cancel tool, but submission is explicitly irreversible, so no obvious workflow dead end exists.