heuristic-mcp

by softerist

Overview Schema Related Servers Score Discussions

JavaScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v3.2.13
Disambiguation4/5
Most tools have distinct purposes, but a_semantic_search and d_find_similar_code both deal with semantic code search, potentially causing confusion. However, descriptions clarify different use cases (query vs. snippet input). The two d-prefixed tools are clearly different.
Naming Consistency4/5
All tool names follow a consistent pattern of a letter prefix followed by an underscore and a descriptive name (e.g., a_semantic_search, b_index_codebase). The pattern is uniform, though the letters themselves have no semantic meaning.
Tool Count4/5
7 tools is a reasonable number for a code search server. The count feels appropriate, covering core functionality without being overly sparse or bloated. The inclusion of e_check_package_version seems slightly out of scope but doesn't harm coherence.
Completeness4/5
The tool set covers essential operations: search, indexing, cache management, configuration, similarity search, and workspace switching. A minor gap is the lack of a tool to inspect or delete specific indexed files, but overall the surface is sufficient for the domain.
Average 4.1/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on February 25, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context that 'stats' is a view action, 'set_ef_search' tunes a parameter, and 'rebuild' forces a rebuild. Annotations already indicate idempotentHint=true, and the description does not contradict any annotations. However, it does not disclose additional behaviors like whether actions are reversible or require permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the overall purpose and then lists actions with concise parenthetical explanations. Every word serves a purpose with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and an enum, the description covers all actions and hints at the efSearch parameter. It does not mention return values, but no output schema exists. It briefly touches on use cases ('tune search accuracy/speed'). A small gap is that it doesn't explicitly state that efSearch only applies to 'set_ef_search', though the schema clarifies this.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides detailed descriptions for both parameters (action enumeration and efSearch range). The main description repeats the action list but does not add new meaning or clarify parameter relationships beyond what the schema offers. With 100% schema coverage, the baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Configure and monitor the ANN (Approximate Nearest Neighbor) search index.' It then enumerates the specific actions ('stats', 'set_ef_search', 'rebuild') with brief explanations, making the tool's function unambiguous. While it doesn't explicitly distinguish from siblings, the unique action set is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus its siblings. It only describes what the tool does, leaving the agent to infer usage context. No explicit when-to-use, when-not-to-use, or alternative tools are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate idempotent=true and destructive=false. The description adds context about cache updates and reindex but does not detail potential side effects like cache invalidation or file system changes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the verb, no fluff. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 params and no output schema, the description covers purpose, directory/cache effect, and reindex option. Could mention path validation but it's sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. The description mentions 'optionally triggers a full reindex' for the reindex parameter but adds no new meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Changes the current workspace path at runtime'), specifies the resource ('workspace path'), and explains the effects ('updates search directory and cache, optionally triggers reindex'). It is distinct from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'Useful for multi-project workflows,' providing some context but no explicit when-to-use or when-not-to-use guidance, nor comparison to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, making safety traits clear. Description adds that it returns semantically similar code chunks but does not disclose performance, size limits, or other behavioral traits beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences total, no filler. First sentence states purpose, second gives use cases. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no output schema, and rich annotations, the description covers purpose and typical use cases. Could mention return format (code chunks) but the description already implies that. Mostly complete for a simple search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage for all three parameters, so the schema already clarifies parameter meaning. Description reiterates 'Given a code snippet' but does not add new semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'find', resource 'similar code patterns', and outcome 'returns other code chunks that are semantically similar'. Distinguishes from sibling tools like a_semantic_search (general search) and b_index_codebase (indexing) by focusing on code pattern similarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases: 'finding duplicate code, understanding patterns, and refactoring opportunities'. However, lacks explicit when-not-to-use guidance or comparison with siblings (e.g., a_semantic_search for non-code text).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by revealing the hybrid search approach (semantic + exact matching), which is behavioral insight beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines the action, second provides use case and output. Efficient, front-loaded, no unnecessary words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage context, output format (snippets with file locations/line numbers). Missing details like result ordering or pagination, but given simplicity and presence of annotations, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so both parameters are documented. The description does not add extra meaning beyond the schema (e.g., it mentions 'query' implicitly but no new details). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'intelligent hybrid code search combining semantic understanding with exact text matching.' It gives concrete examples like 'authentication logic' and specifies the return format. This distinguishes it from siblings like 'd_find_similar_code', which likely focuses on similarity alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains it is 'ideal for finding code by meaning' and works with typos/variations, providing clear usage context. However, it does not explicitly say when not to use it or contrast with alternatives like 'd_find_similar_code'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds context beyond annotations: it updates the embeddings cache. Annotations already note idempotent and not destructive, so no contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first describes action, second provides usage context. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, description fully covers purpose and usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with parameter 'force' described. Description does not add extra meaning beyond schema, baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it triggers a full reindex of the codebase, scanning files and updating embeddings cache. Distinct from siblings like search and cache clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: after large code changes or if index is out of date. Does not mention alternatives but context implies this is the reindex tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true, indicating a safe, read-only, idempotent operation. The description adds behavioral context by stating it fetches from 'official registry' and listing supported registries. No contradictions exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose, second explains usage with registry list and example. No filler; every sentence is essential. Front-loaded with primary action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, no output schema) and the description covers input semantics well. However, it does not describe the return value format (e.g., version string or object). For a tool that fetches version info, specifying the output structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter, 'package', which already describes the prefix pattern. The description expands on this by listing all supported registries and providing multiple concrete examples, adding value beyond the schema by clarifying the range of acceptable prefixes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches the latest version of a package from an official registry. It lists 14 supported registries, making the resource and action unambiguous. Sibling tools are unrelated (e.g., semantic search, index codebase), so there is no confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to use prefixes for different registries with examples like 'pip:requests'. It implicitly covers when to use this tool (checking latest version from official registry) and provides context for correct invocation. However, it does not explicitly state when not to use it or mention alternatives, but the tool is distinct among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true and idempotentHint=true. The description adds value by explaining the reindex consequence and typical scenarios (corruption, codebase changes), extending beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loading the action and consequence, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description fully covers purpose, usage, and behavioral impact, leaving no gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so no additional meaning is needed. The baseline for 0 parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'clears' and the resource 'embeddings cache', with the specific consequence of forcing a complete reindex. It distinguishes from sibling tools like a_semantic_search and b_index_codebase.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context ('when encountering cache corruption or after major codebase changes') but does not mention when not to use or direct alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![heuristic-mcp MCP server](https://glama.ai/mcp/servers/softerist/heuristic-mcp/badges/card.svg)](https://glama.ai/mcp/servers/softerist/heuristic-mcp)

Score Badge

Copy to your README.md:

[![heuristic-mcp MCP server](https://glama.ai/mcp/servers/softerist/heuristic-mcp/badges/score.svg)](https://glama.ai/mcp/servers/softerist/heuristic-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/softerist/heuristic-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server