In-Context — AI-Native Portfolio
Server Details
An interactive portfolio built for AI conversations. Browse work, services, and book calls.
- Status
- Healthy
- Uptime
- 100.0% over 38 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: creating bookings, fetching available slots, and viewing the portfolio. No overlap or ambiguity between them.
All tools follow a consistent verb_noun pattern: booking_create, booking_get_slots, view_portfolio. The naming is predictable and readable.
With 3 tools, the set is well-scoped for a portfolio/booking server. Each tool is essential and there is no bloat.
Core workflows are covered: viewing portfolio and booking a slot. Minor gaps like updating or canceling bookings are not critical for the apparent purpose.
Available Tools
3 toolsbooking_createCInspect
Create a booking at a specific time slot
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Attendee name | |
| Yes | Attendee email | ||
| notes | No | Optional notes about the project | |
| start | Yes | ISO 8601 start time | |
| timezone | No | IANA timezone |
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 only says 'Create a booking,' which implies a write operation, but does not mention side effects (e.g., confirmation emails), failure modes (e.g., slot already taken), permissions, or what the response contains. This is a significant transparency gap for a creation tool.
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, direct sentence with no redundant words. It is front-loaded and efficient, but given the tool's complexity (5 parameters), it is arguably under-specified. Still, it earns its place as a concise purpose statement.
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?
With no output schema and no annotations, the description should explain what happens on success/failure, whether the booking is confirmed, and how it relates to booking_get_slots. It provides none of this, leaving critical gaps for an agent to use the tool correctly.
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?
All five parameters are fully described in the input schema (name, email, notes, start, timezone), so the schema provides the heavy lifting. The description adds no parameter-specific context, but per baseline for high schema coverage, this is acceptable.
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 ('Create') and the resource ('a booking'), and adds 'at a specific time slot' to convey the key input. It is unambiguous and distinguishes from sibling tools by nature of being a create operation, though it does not explicitly mention the siblings.
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 no guidance on when to use this tool versus alternatives. It does not mention that booking_get_slots should be used first to find an available time slot, nor does it state any prerequisites or conditions. This leaves the agent without context for proper tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
booking_get_slotsBInspect
Get available booking time slots for a date range
| Name | Required | Description | Default |
|---|---|---|---|
| endTime | Yes | ISO 8601 end date | |
| timezone | No | IANA timezone | |
| startTime | Yes | ISO 8601 start date |
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 restates the tool name without adding context about return format, authentication needs, timezone handling, or what 'available' means (e.g., excluding already-booked slots). The description is minimal and largely tautological.
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 unnecessary words. It efficiently communicates the core function.
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 is sparse. It omits the return value structure, whether timezone is required for accurate date interpretation, and the behavior when no slots are available. For a simple tool it is minimally viable but leaves notable gaps.
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 already documents all parameters. The description adds only the concept of a 'date range,' which maps to startTime/endTime but does not enhance understanding beyond what the schema provides. 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 'Get available booking time slots for a date range' clearly states a specific verb (Get) and resource (available booking time slots) with scope (date range). It naturally distinguishes itself from siblings like booking_create and view_portfolio.
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 the tool is for checking availability within a date range, which suggests a typical pre-booking step, but it does not explicitly state when to use it versus alternatives or provide exclusions. Sibling tool names hint at use cases but the description itself gives no direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
view_portfolioAInspect
Opens the interactive portfolio, optionally at a specific section. The user can also navigate between sections using tabs inside the portfolio. To jump to a specific section (e.g. the user asks for contact info or work samples), call this again with the section argument — the newest card supersedes older ones. The card's visual appearance (theme, colors, layout) is set by the portfolio owner and cannot be changed via this tool.
| Name | Required | Description | Default |
|---|---|---|---|
| section | No | Section to open the portfolio at (default: home) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses that the newest card supersedes older ones when called again, and that visual appearance cannot be changed. These are meaningful behavioral traits beyond the schema.
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 well-structured sentences, each adding essential information: the action, navigation capability, re-invocation semantics, and a limitation. No fluff, and the main 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 tool with one optional parameter and no output schema, the description covers all needed aspects: open action, section navigation, re-call behavior, and immutability of appearance. Complete and self-sufficient.
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 fully documents the section parameter with enums and a default, so the baseline is 3. The description adds value by giving concrete use examples (contact, work) and explaining the superseding behavior when re-invoked, which is not 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 explicitly states the tool 'Opens the interactive portfolio' with an optional section, using a specific verb and resource. This clearly distinguishes it from the sibling booking 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?
It provides explicit guidance to call again with the section argument to jump to a specific section, and notes that users can navigate via tabs, implying the tool is not needed for tab navigation. While no direct alternative is named, the context makes usage 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.
1 tool update
- Changed
view_portfolio1 field changed- added
Input schema / properties / sectionAdded value: +{ + "description": "Section to open the portfolio at (default: home)", + "enum": [ + "home", + "work", + "services", + "about", + "contact" + ], + "type": "string" +}
1 tool update
- Changed
booking_create1 field changed- added
Input schema / properties / notesAdded value: +{ + "description": "Optional notes about the project", + "type": "string" +}
2 tool updates
- Added
booking_create - Added
booking_get_slots
1 tool update
- Changed
view_portfolio2 fields changed- removed
Input schema / $schemaRemoved value: -"http://json-schema.org/draft-07/schema#" - added
Input schema / requiredAdded value: +[]
1 tool update
- First observed
view_portfolio
Related MCP Connectors
Build and publish websites through AI conversation.
The first portfolio AI agents can hire. Profile, products, pricing and briefs over MCP.
Build, edit, and publish real websites and online stores by chatting with your AI assistant.
Build, version, review, and export websites, web apps, and games from a conversation.
Related MCP Servers
- AlicenseAqualityCmaintenanceEnables searching and retrieving portfolio data including experience, skills, and contact information through natural language queries.5MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to answer questions about a person's portfolio by exposing projects, experience, skills, and searchable content through the Model Context Protocol.9 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables AI assistants and LLM clients to query a professional CV and portfolio, including work history, technical skills, projects, job compatibility evaluation, education, and contact details.MIT
- FlicenseNot gradedqualityBmaintenanceEnables MCP-compatible AI clients to query structured portfolio data such as experience, projects, skills, contact info, and blog posts without scraping HTML.-
Glama MCP Gateway
Add one secure layer between your agents and this server.