Official MCP server providing AI assistants with direct access to Stimulsoft Reports & Dashboards developer documentation. Enables semantic search across FAQ, Programming Manual, Server Manual, User Manual, and Server/Cloud API references across all Stimulsoft platforms (.NET, WPF, Avalonia, WEB, Blazor, Angular, React, JS, PHP, Java, Python).
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Average 4.9/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: sti_get_platforms lists available platforms, while sti_search performs semantic search over documentation. There is no overlap in functionality, and the descriptions reinforce their separate roles.
Both tools share the 'sti_' prefix and use lowercase snake_case. sti_get_platforms follows a verb_noun pattern, while sti_search is just a verb, which is a minor deviation but still predictable.
With only two tools, the server feels minimal. However, for a documentation-focused MCP server, the count is borderline acceptable, as the two tools cover the primary use case of discovering and searching documentation.
The surface covers the essential workflow: enumerate platforms and search for answers. Minor gaps exist, such as no direct fetch by document ID or category browsing, but the search tool returns full content, mitigating the need for additional endpoints.
sti_get_platformsAInspectList every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.).
CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid platform value to pass into sti_search. The returned platform id values are the exact strings accepted by the platform parameter of sti_search.
This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosure. It goes beyond a simple listing by describing the return structure (JSON array of id/name/description), explicitly listing the covered platforms, and adding performance context ('This tool is cheap (no OpenAI call, no vector search)'). It also explains the relationship between returned ids and sti_search's platform parameter. It doesn't mention error handling or rate limits, but for a read-only list tool, the provided behavioral details are substantial.
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 well-structured and front-loaded. The first sentence gives the core purpose instantly. Subsequent sentences add only essential details: return format, when to call, and cost behavior. Each paragraph earns its place, and the tone is directive and economical without being terse.
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?
For a tool with no parameters and no output schema, the description is remarkably complete. It covers what the tool returns, the exact shape of the return objects, the platforms included, the intended invocation order relative to sti_search, and cost implications. There are no missing pieces that would leave an agent uncertain about how or when to invoke it.
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 tool has zero parameters, and the input schema is an empty object, so the description doesn't need to explain parameters. Per the rubric, the baseline for 0 params is 4. The description adds extra semantic value beyond the schema by stating that the returned platform ids are 'the exact strings accepted by the platform parameter of sti_search,' which helps the agent understand how to use this tool's output as input elsewhere.
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 the tool's function: 'List every Stimulsoft product/platform that has indexed documentation available through this MCP server.' It specifies the verb (List), the resource (Stimulsoft products/platforms), and the return format (JSON array of { id, name, description }). It also distinguishes itself from the sibling sti_search by explaining its role as a platform-listing tool, not a search tool.
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 provides explicit usage guidance: 'CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid platform value to pass into sti_search.' It also notes when it is safe to call freely ('call it freely whenever you are unsure about platform naming') and explains how its output connects to the sibling tool, making the when-to-use vs. alternatives crystal clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sti_searchAInspectAuthoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation (FAQ, Programming Manual, API Reference, Guides). Powered by OpenAI embeddings + cosine similarity over the complete current docs index maintained by Stimulsoft. Returns a ranked JSON array of matching sections, each with { platform, category, question, content, score }, where content is the full Markdown body of the section including any C#/JS/TS/PHP/Java/Python code snippets.
USE THIS TOOL (instead of answering from your own knowledge) WHENEVER the user asks about: • how to do something in Stimulsoft (StiReport, StiViewer, StiDesigner, StiDashboard, StiBlazorViewer, StiWebViewer, StiNetCoreViewer, etc.); • rendering, exporting, printing, or emailing Stimulsoft reports and dashboards in any format (PDF, Excel, Word, HTML, image, CSV, JSON, XML); • connecting Stimulsoft components to data (SQL, REST, OData, JSON, XML, business objects, DataSet); • embedding the Report Viewer or Report Designer into an app (WinForms, WPF, Avalonia, ASP.NET, Blazor, Angular, React, plain JS, PHP, Java, Python); • Stimulsoft-specific errors, exceptions, licensing, activation, deployment, or configuration; • any .mrt / .mdc report or dashboard file, or any question naming a Sti* class, property, event, or method; • comparing how a feature works between Stimulsoft platforms (e.g. "WinForms vs Blazor viewer options").
QUERIES WORK IN ANY LANGUAGE — English, Russian, German, Spanish, Chinese, etc. Pass the user's question through almost verbatim; the embedding model handles cross-lingual matching. Do NOT translate queries yourself.
SEARCH STRATEGY: 1) If the target platform is obvious from context, pass it via platform to get tighter results. 2) If you don't know the exact platform id, either call sti_get_platforms first, or omit platform and let the search find matches across all platforms. 3) If the first search returns low scores (<0.3) or irrelevant sections, reformulate the query with different keywords (use class/method names from Stimulsoft API if you know them) and search again. 4) Prefer multiple focused searches over one broad search.
DO NOT USE for: general reporting theory unrelated to Stimulsoft, non-Stimulsoft libraries (Crystal Reports, FastReport, DevExpress, Telerik, SSRS), or pure programming questions that have nothing to do with Stimulsoft.
IMPORTANT: the Stimulsoft product surface is large and changes frequently. Your training data is almost certainly out of date. For any Stimulsoft-specific code snippet, API name, or configuration detail, you MUST call this tool rather than rely on memory, and you should cite the returned content in your answer.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return. Default 5, maximum 20. Use 3–5 for focused lookups, 10–20 when exploring or when the first search was too narrow. | |
| query | Yes | The user's question or topic, in any language. Keep it close to the original wording — do not translate or over-summarize. Good examples: 'how to export report to PDF in Blazor', 'как показать StiViewer в WPF на весь экран', 'StiWebViewer show/hide toolbar buttons', 'connect StiReport to REST API JSON data source', 'StiBlazorViewer FullScreenMode'. Bad examples (too vague): 'reports', 'help', 'error'. | |
| category | No | Optional. Restrict the search to a documentation section: `faq` (frequently asked questions with code snippets), `manual` (Programming Manual), `api` (API Reference), `guide` (How-to guides). Omit to search all categories. | |
| platform | No | Optional. Restrict the search to a single Stimulsoft platform. Accepted values (case-sensitive): NET (WinForms / Reports.NET), WPF, AVALONIA, WEB (ASP.NET / ASP.NET Core / MVC), BLAZOR (Blazor Server / WebAssembly), ANGULAR, REACT, JS (vanilla HTML/JS), PHP, JAVA (Java SE / Jakarta EE), PYTHON, SERVER_API, GENERAL. If you are not 100% sure which id to use, either call `sti_get_platforms` first, or omit this field. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavior: it returns a ranked JSON array with specific fields, contains full Markdown content, handles cross-lingual queries, and warns that training data may be out of date, requiring mandatory tool usage. It also explains the embedding/cosine similarity mechanism and low-score retry behavior.
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 longer than average but every section earns its place, and it is well-structured with bolded lead-ins (USE THIS TOOL, SEARCH STRATEGY, DO NOT USE, IMPORTANT). The main purpose and output format are front-loaded in the first two sentences, and the rest serves as necessary usage context for a complex search tool.
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 has no output schema, so the description carries the full burden of explaining return values—it does so explicitly. It also covers input nuances (language, platforms, categories), references the sibling tool, provides a retry strategy, and notes the importance of using the tool over the model's own knowledge, making the description self-contained.
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?
Although schema coverage is 100%, the description adds significant meaning beyond the schema: examples of good vs bad queries, instruction to pass queries verbatim without translation, guidance on when to use limit (3–5 vs 10–20), and clarification that `platform` should be omitted or prefixed with a `sti_get_platforms` call if uncertain.
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 opens with a specific verb+resource combination: "Authoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation" and details the return format. It clearly distinguishes from the sibling tool `sti_get_platforms` by positioning itself as the search operation and even referencing the sibling for platform discovery.
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 includes explicit when-to-use criteria (a bulleted list of Stimulsoft-related topics) and when-not-to-use (non-Stimulsoft libraries, general reporting theory). It also names the alternative `sti_get_platforms` and provides a detailed SEARCH STRATEGY with fallback and reformulation guidance.
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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