count_text_statsReturn word count, character count, sentence count, and paragraph statistics for a given text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to summarize |
| Name | Required | Description | Default |
|---|---|---|---|
| word_count | Yes | ||
| sentence_count | Yes | ||
| character_count | Yes | ||
| paragraph_count | Yes | ||
| average_words_per_sentence | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / additionalPropertiesRemoved value: -falseInput schema / properties / text / titleAdded value: +"Text"Input schema / titleAdded value: +"mcp_count_text_statsArguments"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals a non-destructive operation. The description adds detail about what the tool returns (word, character, sentence, paragraph stats), giving the agent a clear behavioral expectation. It does not dive into tokenization edge cases or the exact meaning of 'paragraph statistics,' but for a tool of this simplicity, the added context is valuable.
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 that directly lists the tool's outputs. Every word earns its place; there is no redundancy or fluff, making it both concise and well-structured.
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 low complexity, the presence of a readOnlyHint, and an output schema (which presumably defines return values), the description is complete enough for an agent to select and invoke the tool correctly. It covers the essence without needing to restate schema details.
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 100% coverage: the only parameter 'text' is described as 'Text to summarize,' and the tool description says 'for a given text,' so the parameter's purpose is clear. The description does not add significantly beyond the schema (e.g., formats, length limits), but the schema already handles this adequately.
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 specifies a concrete verb ('Return') and enumerates the specific outputs (word count, character count, sentence count, paragraph statistics). It unambiguously identifies a text-analysis tool that is distinct from all sibling tools, which are blockchain/defi/web utilities.
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 does not explicitly state when to use this tool vs alternatives, nor does it offer any exclusions or prerequisites. However, the purpose is self-evident: when the agent needs text metrics, this is the obvious choice. This makes usage guidelines only implied rather than explicitly articulated.
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.
Most tools target distinct data sources, but several near-duplicates exist: get_token_approvals/get_wallet_approvals, get_defi_positions/get_wallet_positions, and get_wallet_portfolio/get_eth_balance. The descriptions do cross-reference and clarify the differences, so an agent can disambiguate with effort, but names alone are not enough.
The dominant get_<noun> pattern is clear and nearly all names use lowercase snake_case with verb-first conventions. A few tools like calculate, record_predictions, http_fetch, and web_search break the get_ pattern, but the overall style remains predictable.
34 tools is excessive for a single server, even for a broad DeFi/onchain analytics domain. The count is inflated by generic utilities such as calculate, count_text_stats, web_search, and http_fetch, plus multiple overlapping data-retrieval endpoints, making the surface hard to scan.
The set covers an unusually wide range of domain operations: prices, balances, portfolio/positions, approvals, yields, TVL, DEX quotes/volume, transactions, blocks, gas, ENS, contract reads, and risk assessments. It is view-only by design, so missing write/transaction tools is acceptable; minor gaps like address-based token pricing or transaction simulation are workaround-able.