get_driversList F1 drivers entered in a session (live race data): number, full name, 3-letter acronym, team, team colour, country, headshot. session_key="latest" for the most recent / ongoing session.
| Name | Required | Description | Default |
|---|---|---|---|
| session_key | No | Session key, or 'latest' for the most recent session. Default 'latest'. | |
| driver_number | No | Restrict to a single driver, e.g. 1, 44. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "session_key": "latest"
+ },
+ {
+ "driver_number": 44,
+ "session_key": 9876
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds 'live race data,' which implies real-time, and lists return fields, providing context beyond annotations but not introducing new behavioral concerns.
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, focused sentence that front-loads the core action and includes essential details (fields, session_key tip). Every word earns its place; no 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?
Given the lack of an output schema, the description adequately explains the return fields and parameter behavior. The tool is low-complexity (0 required params, no nested objects), and the description covers all necessary context for an agent to use it 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?
Schema description coverage is 100%; the description merely restates the schema's parameter explanations (e.g., session_key='latest'). It does not add additional semantic value beyond what the input schema already provides.
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 ('List') and resource ('F1 drivers entered in a session'), clearly stating the scope ('live race data') and enumerating the fields returned. This distinguishes it from sibling tools like get_laps or get_sessions.
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 when to use (to list drivers for a session) and provides a practical tip (session_key='latest'). It does not explicitly state when not to use or list alternatives, but the sibling set is distinct enough for an agent to infer appropriate usage.
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.
Several tool clusters have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions across the same 5,756-tool catalog, and ask_pipeworx_beta is explicitly identical to ask_pipeworx right now. The polymarket_* family also overlaps heavily (edges, arbitrage, fill_risk, kalshi_spread all surface tradeable discrepancies), and entity_profile/compare_entities/recent_changes all fan out to overlapping SEC/news/patent sources. Descriptions are detailed, but the set contains intentional near-duplicates that make selection genuinely ambiguous.
Naming follows no single convention: get_drivers/get_laps/get_meetings/get_sessions use verb_noun, polymarket_arbitrage/polymarket_edges are noun-phrase domain prefixes, pipeworx_feedback/pipeworx_trending use a vendor prefix, remember/recall/forget are bare verbs, and ask_pipeworx variants mix with action phrases like discover_tools, deep_research, and validate_claim. The inconsistency makes it harder to predict related tool names.
35 tools is heavy, and the count is severely mismatched to the server name 'Openf1': only 4 of 35 tools (get_drivers, get_laps, get_meetings, get_sessions) are actually F1-related, while the other 31 are a general-purpose Pipeworx data/prediction-market platform. The number itself could be reasonable for a broad data hub, but for an F1 server it is bloated with unrelated functionality.
For the stated F1 domain, the surface is severely incomplete: it covers meetings, sessions, drivers, and laps but lacks race results, qualifying results, standings, pit stops, or constructor data — major gaps for any F1 use case. The Pipeworx side is far more complete (query, research, entities, verification, memory, subscriptions), but that completeness doesn't serve the server's apparent purpose.