mergers_acquisitionsFinancial Modeling Prep recent M&A activity feed: announced deals with acquirer, target, value, date. Use for "who did $TICKER acquire", "recent deals in sector X", deal-flow monitoring.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering safety and mutation concerns. The description adds that it is a feed of announced deals, but does not disclose behavior like pagination limits or return format. Given annotation coverage, this is adequate but not rich.
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 two sentences long and immediately communicates the tool's purpose and use cases. It is front-loaded with the core function and contains no superfluous information.
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 is simple with one optional parameter and no output schema. The description explains the data content (acquirer, target, value, date) and use cases, but it does not describe how the 'page' parameter affects results or what the response structure looks like. This is a noticeable gap.
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?
There is one parameter, 'page', with no description in the schema (0% schema coverage). The description does not mention this parameter at all, leaving its purpose and usage entirely undocumented. The description fails to compensate for the lack of schema 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 clearly states what the tool does: it provides a recent M&A activity feed with announced deals including acquirer, target, value, and date. It also gives specific use cases, which helps distinguish it from sibling financial data tools, though it does not explicitly name an alternative.
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 explicit use cases: 'who did $TICKER acquire', 'recent deals in sector X', and deal-flow monitoring. This provides clear context for when to use the tool, but it does not mention when not to use it or direct users to an alternative tool.
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.
Multiple tools overlap in purpose: quote/quote_short/historical_price/intraday for price data; balance_sheet/income_statement/cash_flow for financials; search_symbol/search_name/discover_tools for lookup; and a cluster of Pipeworx routers (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim) with unclear boundaries. Agents will frequently select the wrong tool.
All tool names use consistent snake_case, but naming conventions vary widely: noun phrases (balance_sheet, entity_profile), bare verbs (forget, subscribe), verb+noun (compare_entities, resolve_entity), and adjective+noun (historical_price, recent_alerts). No single pattern dominates, making it harder to guess tool names.
55 tools is excessive for a server labeled 'Fmp'. The core financial data tools are perhaps 20-25, while the rest are unrelated: memory utilities, prediction market analyzers, web scraping, and meta-routing tools. This bloated set dilutes the server's purpose and burdens the agent with irrelevant options.
For the declared domain (FMP financials), the set covers the main statements but lacks tools like segment data, insider trades (listed as paid), or ownership details (also paid). Conversely, it includes many tools for prediction markets and general data retrieval that don't belong here, creating a mismatch between server name and actual capability.