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njoerd114

kubecon-eu-mcp

by njoerd114

search_sessions

Find KubeCon Europe sessions by keyword, topic, speaker, or technology. Filter by day and track to locate relevant presentations quickly.

Instructions

Search conference sessions by keyword, topic, speaker name, or technology.

Args: query: Search query (e.g., "eBPF", "security", "AI agents", "platform engineering"). day: Optional day filter: "monday", "tuesday", "wednesday", "thursday". track: Optional track filter (e.g., "Keynote", "Tutorial", "Breakout"). limit: Maximum number of results to return (default 20).

Returns: JSON array of matching sessions with title, speakers, time, room, and URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
dayNo
trackNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The MCP tool handler for 'search_sessions', which delegates the search logic to the data_service.
    @mcp.tool()
    async def search_sessions(
        query: str,
        day: str = "",
        track: str = "",
        limit: int = 20,
    ) -> str:
        """Search conference sessions by keyword, topic, speaker name, or technology.
    
        Args:
            query: Search query (e.g., "eBPF", "security", "AI agents", "platform engineering").
            day: Optional day filter: "monday", "tuesday", "wednesday", "thursday".
            track: Optional track filter (e.g., "Keynote", "Tutorial", "Breakout").
            limit: Maximum number of results to return (default 20).
    
        Returns:
            JSON array of matching sessions with title, speakers, time, room, and URL.
        """
        results = await data_service.search_sessions(
            query=query,
            day=day or None,
            track=track or None,
            limit=limit,
        )
        if not results:
            return json.dumps(
                {
                    "message": f"No sessions found for '{query}'.",
                    "suggestion": "Try broader terms or remove day/track filters.",
                }
            )
        return json.dumps([s.to_dict() for s in results], indent=2)
  • The actual implementation of the session search logic, residing within the DataService class.
    async def search_sessions(
        self,
        query: str,
        day: str | None = None,
        track: str | None = None,
        limit: int = 20,
    ) -> list[Session]:
        """Search sessions by keyword, optionally filtered by day and track."""
        sessions = await self.get_sessions()
        if day:
            all_sessions = sessions + (
                await self.get_colocated_sessions() if day == "monday" else []
            )
        else:
            all_sessions = sessions + await self.get_colocated_sessions()
    
        query_lower = query.lower()
        results = []
    
        for s in all_sessions:
            if day and s.day != day.lower():
                continue
            if track and track.lower() not in s.category.lower():
                continue
    
            # Search across title, description, speakers, category
            searchable = (
                f"{s.title} {s.description} {' '.join(s.speakers)} {s.category}".lower()
            )
            if query_lower in searchable:
                results.append(s)
    
        return results[:limit]
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the return format ('JSON array of matching sessions') and default behavior ('limit' default is 20), but lacks details on permissions, rate limits, error handling, or pagination. It's adequate but not rich in behavioral context.

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

Conciseness5/5

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

The description is well-structured with a clear purpose statement, organized 'Args' and 'Returns' sections, and no wasted words. Every sentence adds value, making it easy to scan and understand.

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

Completeness4/5

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

Given 4 parameters with 0% schema coverage and an output schema (implied by 'Returns'), the description is mostly complete. It covers parameter semantics and return format, but lacks behavioral details like error cases or performance limits, which would be helpful for a search tool.

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

Parameters4/5

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. It adds meaning for all parameters: 'query' with examples, 'day' with allowed values, 'track' with examples, and 'limit' with default. However, it doesn't specify constraints like 'day' enum validation or 'limit' range, leaving some gaps.

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?

The description clearly states the tool's purpose with a specific verb ('Search') and resource ('conference sessions'), plus search criteria ('by keyword, topic, speaker name, or technology'). It distinguishes from siblings like 'get_schedule' (which likely returns a full schedule) and 'score_sessions' (which likely rates sessions).

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

Usage Guidelines3/5

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

The description implies usage for searching sessions with specific filters, but doesn't explicitly state when to use this vs. alternatives like 'get_schedule' (for full schedule) or 'find_speaker' (for speaker-focused queries). No exclusions or prerequisites are mentioned.

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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