decode_jwtDecode a JSON Web Token (keyless, offline): returns the header and payload JSON plus a summary of the standard claims (iss, sub, aud, exp/iat/nbf as ISO dates, and whether it is expired). NOTE: this decodes but does NOT verify the signature — a decoded token is not a verified/trusted token.
| Name | Required | Description | Default |
|---|---|---|---|
| token | Yes | A JWT (header.payload.signature). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "token": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxNTE2MjM5MDIyfQ.SflKxwRJSMeKKF2QT4fwpMeJf36POk6yJV_adQssw5c"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds value beyond annotations by stating it is keyless, offline, and lists output specifics (header, payload, ISO date claims, expiration check). The annotation contradiction is false. It clearly describes behavior without contradicting annotations.
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 concise with two sentences plus a critical note. It is front-loaded with the main action and output, followed by an important caution. No unnecessary words.
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 description adequately covers the tool's purpose, output, and limitations despite no output schema. It mentions the output content (header, payload, summary) and expiry check. Missing details about error handling are minor for a simple decode tool.
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 coverage is 100% with a single 'token' parameter described. The description does not add extra detail about the parameter beyond the schema, so a baseline of 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 title and description clearly state the verb 'decode' and resource 'JWT'. It specifies what is returned (header, payload, summary of claims) and distinguishes from siblings by its unique function. No other sibling tool decodes JWTs.
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 explicitly notes that the tool decodes but does NOT verify the signature, guiding the agent to use it for inspection only and not for trust verification. It implies appropriate usage contexts (offline, keyless) without alternatives needed due to no similar tools.
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 have unclear boundaries. ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route natural-language queries to the same underlying catalog, with ask_pipeworx_beta currently documented as identical to ask_pipeworx. The Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) also overlaps in purpose, leaving an agent to parse fine-grained differences before selecting.
All tool names use snake_case and several share recognizable prefixes (ask_pipeworx_*, polymarket_*), which helps readability. However, the verb/noun order is inconsistent—compare_entities vs entity_profile, bet_research vs deep_research, scan_competitor_ai_presence vs ai_visibility_check—and bare verbs like remember, forget, and subscribe mix with noun-first names.
32 tools is well above the 25-tool threshold for a coherent set. The bloat is worse because the server is named 'Jwt' but only one tool relates to JWT; the rest cover unrelated domains such as data routing, prediction markets, memory, subscriptions, and npm scanning, so the count is neither scoped to the server's name nor internally cohesive.
For a server named 'Jwt', the surface is severely incomplete: only decode_jwt is present, with no sign, verify, encode, or refresh tools, so common JWT workflows dead-end. Even when judged as a general Pipeworx data toolkit, the mismatch between the server name and the actual tool surface creates a significant gap for agents expecting JWT functionality.