Codacy MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Codacy MCP Serverrun a security audit on my repository"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Codacy MCP Server โ Vurb.ts Edition
The official Codacy MCP Server reimagined with the Vurb.ts framework โ structured perception for AI agents.
11 Tools - 44 actions available on-demand
Related MCP server: CodeAlive MCP
3 Prompts MCP prompts โ code-review, security-audit, repo-health
๐ค Zero lines of human code.
An AI agent (Antigravity, Opus 4.6) read a framework's llms.txt and a 488-line skill file. That's all it knew about Vurb.ts.
From that, it built a complete production codebase from scratch:
11 tools ยท 44 actions ยท 12 models ยท 11 presenters ยท 3 prompts ยท 105 tests
No human wrote a single line.
The thesis of Vurb.ts: if an AI agent can learn a framework from its llms.txt and produce production-grade code on the first attempt โ the framework is doing its job.
๐ Designed for agents, not for humans.
Traditional frameworks optimize for human ergonomics โ tutorials, documentation, months of learning curve. Vurb.ts inverts this entirely. Its fluent API, llms.txt, and skill system were designed so that an AI agent can become productive in a single context window. The learning curve isn't short โ it's zero. The agent reads the spec, understands the patterns, and ships. This codebase is the proof.
Why Vurb.ts?
The original Codacy MCP Server is a solid, production-grade implementation. This edition rebuilds it using the Vurb.ts MVA (Model ยท View ยท Agent) pattern โ a framework designed specifically for MCP servers that gives AI agents structured, high-fidelity perception instead of raw JSON dumps.
Key advantages of the Vurb.ts approach:
๐ง Structured Perception โ Presenters transform raw API data into optimized, LLM-readable formats with semantic annotations, HATEOAS navigation links, and severity-based suggestions
๐ก๏ธ Guardrails โ Middleware (
requireAuth), egress limits, idempotent mutation markers, and DLP redaction (secrets are stripped before reaching the wire)๐ Prompt Templates โ First-class support for MCP prompts (
code-review,security-audit,repo-health) with dynamic argument injection๐ State Sync โ Declarative cache invalidation policies ensure mutations automatically refresh dependent queries
๐งฉ Fluent API โ Each tool action is defined as a composable, type-safe chain โ no manual JSON schemas or handler wiring
๐ฆ Zero Code Generation โ No auto-generated OpenAPI client; a lightweight typed HTTP client is all that's needed
๐๏ธ Grouped Exposition โ 44 actions exposed as 11 namespace tools, avoiding context window explosion
Capability Matrix
Capability | Original | Vurb.ts |
Security & DLP | ||
Auth middleware with self-healing errors | โ | โ |
Secret redaction before wire (DLP) | โ | โ |
Egress size limits per action | โ | โ |
Safe process execution ( | โ | โ |
Determinism & Guardrails | ||
Typed input schemas (Zod) | โ | โ |
Idempotent mutation markers | โ | โ |
Declarative cache invalidation | โ | โ |
| โ | โ |
Tool-redirection hints (cross-agent navigation) | โ | โ |
LLM Optimization | ||
Grouped tool exposition (โ78% context tokens) | โ | โ |
HATEOAS navigation links in responses | โ | โ |
Severity-aware action suggestions | โ | โ |
Presenter-formatted tables (vs raw JSON) | โ | โ |
MCP Protocol | ||
| โ | โ |
| โ | โ |
| โ | โ |
State sync / cache control headers | โ | โ |
Developer Experience | ||
Auto-discovery (zero manual imports) | โ | โ |
Fluent builder API | โ | โ |
Test suite (105 tests) | โ | โ |
Hot-reload dev server | โ | โ |
Grouped Tool Exposition โ Solving Context Explosion
This is the single most important architectural difference between the two implementations.
The Problem
The original server registers 24 flat tools in the MCP tools/list response. Every one of them โ with its full name, description, and JSON Schema โ is injected into the LLM's system prompt at the start of every conversation. This means the model must process ~4,000 tokens of tool definitions before the user even types a word.
At 44 actions, a flat approach would be even worse โ ~7,000+ tokens consumed permanently just by tool schemas, leaving less room for actual conversation and reasoning.
The Solution: toolExposition: 'grouped'
Vurb.ts introduces grouped tool exposition. Instead of exposing 44 individual tools, the MCP server advertises only 11 namespace routers:
Original (flat) Vurb.ts (grouped)
โโโโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโ
codacy_list_organizations codacy_organizations โ 2 actions
codacy_list_organization_repos codacy_repositories โ 3 actions
codacy_list_repository_issues codacy_issues โ 7 actions
codacy_search_org_srm_items codacy_security โ 6 actions
codacy_search_repo_srm_items codacy_tools โ 6 actions
codacy_list_files codacy_files โ 4 actions
codacy_get_file_issues codacy_pull_requests โ 6 actions
codacy_get_file_coverage codacy_commits โ 3 actions
codacy_get_file_clones codacy_overview โ 2 actions
codacy_get_file_with_analysis codacy_quality โ 3 actions
codacy_list_repository_pull_reqs codacy_cli โ 2 actions
codacy_get_repository_pull_req โโโโโโโโโโโโโโโโโโโโโโ
codacy_list_pull_request_issues 11 tools in system prompt
44 actions available on-demand
codacy_get_pr_files_coverage
codacy_get_pr_git_diff
codacy_get_repository_analysis
codacy_list_tools
codacy_list_repo_tools
codacy_get_pattern
codacy_list_repo_tool_patterns
codacy_get_issue
codacy_setup_repository
codacy_cli_analyze
codacy_cli_install
โโโโโโโโโโโโโโโโโโโโโ
24 tools in system promptHow the LLM Navigates
The model interacts with the 11 namespace tools using an action parameter. It works like a progressive disclosure pattern:
Step 1 โ Discovery. The LLM sees 11 high-level tools with concise descriptions. Each tool's schema has an action enum listing available actions:
codacy_security โ actions: [search_org, search_repo, dashboard, sbom_search, ossf_scorecard, ignore]Step 2 โ Selection. When the user asks "show me security vulnerabilities in my repo", the LLM picks codacy_security with action: "search_repo". The remaining 43 action schemas are never loaded into context.
Step 3 โ Navigation. Presenters include HATEOAS-style links in their response, guiding the LLM to the next logical tool:
๐ Next steps: codacy_issues.list (for code quality) ยท codacy_security.dashboard (for summary)Context Window Impact
Metric | Original (flat) | Vurb.ts (grouped) |
Tools in | 24 | 11 |
Actions available | 24 | 44 (+83%) |
JSON Schema surface (tool definitions) | 29,316 chars across 718 lines | Derived from fluent chain โ no hand-written schemas |
Fewer tools in the system prompt means the LLM spends less context budget on tool schemas and more on actual reasoning โ a critical advantage for models with limited context windows.
Developer Experience โ Side by Side
The same security search tool in both implementations:
// tools/searchSecurityItemsTool.ts (124 lines)
export const searchRepositorySecurityItemsTool = {
name: toolNames.CODACY_LIST_REPOSITORY_SRM_ITEMS,
description: `Tool to list security...
\n ${rules}
\n ${generalRepositoryMistakes}`,
inputSchema: {
type: 'object',
properties: {
...repositorySchema,
...getPaginationWithSorting('...'),
options: {
type: 'object',
properties: {
priorities: {
type: 'array',
items: { type: 'string',
enum: ['Low','Medium','High','Critical']
},
},
scanTypes: { /* ... 20 more lines */ },
categories: { /* ... 15 more lines */ },
statuses: { /* ... 8 more lines */ },
},
},
},
required: ['provider','organization','repository'],
},
};
// handlers/security.ts (35 lines)
export const handler = async (args: any) => {
const { provider, organization, repository,
cursor, limit, sort, direction, options
} = args;
return await SecurityService.searchSecurityItems(
provider, organization,
cursor, limit, sort, direction,
{ ...options, repositories: [repository] }
);
};
// index.ts โ manual tool registration
codacy_search_repository_srm_items: {
tool: Tools.searchRepositorySecurityItemsTool,
handler: Handlers.searchRepoSecurityItemsHandler,
},// codacy_security.tool.ts โ complete
export const searchRepo = security
.query('search_repo')
.describe('Search security findings within a repository.')
.instructions(`Repo-level security search.
Uses the organization-level API filtered by repo.
Scan types: SAST, SCA, Secrets, IaC, CICD.
DAST and PenTesting are org-level only.`)
.fromModel(CodacyScopeModel, 'repo')
.withOptionalEnum('priority', SEVERITY_LEVELS)
.withOptionalEnum('category', SECURITY_CATEGORIES)
.withOptionalEnum('scanType', REPO_SCAN_TYPES)
.withOptionalEnum('status', SECURITY_STATUSES)
.withOptionalNumber('cursor')
.withOptionalNumber('limit')
.egress(1 * 1024 * 1024)
.returns(SecurityPresenter)
.handle(async (input, ctx) => {
const body = { repositories: [input.repository] };
if (input.priority) body.priorities = [input.priority];
if (input.category) body.categories = [input.category];
return ctx.client.post(
`organizations/${input.provider}/${input.organization}/security/search`,
body,
{ cursor: input.cursor, limit: input.limit ?? 50 },
);
});What you don't write with Vurb.ts:
โ No JSON Schema objects โ input types derived from fluent chain
โ No handler wiring โ
autoDiscover()replaces manual registrationโ No OpenAPI codegen โ lightweight HTTP client replaces 3,000+ generated lines
โ No
anytypes โ full type inference from model to presenter
๐ What Reaches the LLM โ The Security Gap
The original server sends every API field directly to the LLM provider via JSON.stringify (index.ts:172). No filtering, no size limit, no redaction.
Here is what happens to each field from a Secrets detection scan:
API Field | โ Without Vurb.ts | โ With Vurb.ts | How |
|
|
| โ |
|
|
| Presenter |
| โ ๏ธ |
|
|
| โ ๏ธ | Gone โ never serialized | Schema stripping |
| โ ๏ธ | Gone โ never serialized | Schema stripping |
| โ ๏ธ | Gone โ never serialized | Schema stripping |
| โ ๏ธ Full internal API surface โ sent to LLM | Gone โ never serialized | Schema stripping |
247 findings | All 247 dumped (1,000+ lines) | Top results only |
|
Response size | Unbounded | Max 1 MB |
|
Next action | LLM must guess |
|
|
Architecture Comparison
Metrics (verified)
Every number below was measured directly from the source code.
Metric | Original | Vurb.ts | Diff |
Source files (hand-written) | 45 | 42 | โ3 |
Tool definitions ( | 718 lines | โ | โ |
Handlers ( | 424 lines | โ | โ |
Agents ( | โ | 763 lines | โ33% vs tools+handlers |
Tools in | 24 | 11 | โ54% |
Actions available to the LLM | 24 | 44 | +83% |
MCP Prompts | 0 | 3 | +3 |
Test cases | 0 | 105 | +105 |
Runtime dependencies | 6 | 4 | โ33% |
Dev dependencies | 9 | 3 | โ67% |
Tool Actions (44)
codacy_organizations (2)
Action | Description |
| List organizations the authenticated user belongs to |
| List repositories in an organization |
codacy_repositories (3)
Action | Description |
| Get repository details with analysis metrics |
| List branches of a repository |
| Add or follow a repository (multi-step orchestration) |
codacy_issues (7)
Action | Description |
| Search and filter code quality issues |
| Get detailed issue information |
| Get issues for a specific file |
| Get issues in a pull request |
| Download auto-fix patches |
| Mark an issue as ignored |
| Batch ignore multiple issues |
codacy_security (6)
Action | Description |
| Search org-level security findings |
| Search repo-specific security findings |
| Get security dashboard summary |
| Search SBOM dependencies |
| Get OSSF Scorecard for a package/repo |
| Ignore a security finding |
codacy_tools (6)
Action | Description |
| List all analysis tools available |
| List tools configured for a repository |
| Get a specific code pattern definition |
| List patterns for a tool in a repository |
| Enable/disable a tool for a repository |
| Enable/disable specific patterns |
codacy_files (4)
Action | Description |
| List files with analysis metrics |
| Get file details with metrics |
| Get line-by-line coverage |
| Get code duplication blocks |
codacy_pull_requests (6)
Action | Description |
| List PRs with analysis status |
| Get PR details with quality results |
| Get file-level PR coverage |
| Get the Git diff |
| Trigger AI-powered code review |
| Bypass the quality gate |
codacy_commits (3)
Action | Description |
| List commits with analysis status |
| Get commit details with delta statistics |
| Get issues introduced by a commit |
codacy_overview (2)
Action | Description |
| Aggregated issue overview with charts |
| Issue count breakdown by category |
codacy_quality (3)
Action | Description |
| Get quality gate thresholds for a repository |
| List gate policies for an organization |
| Get details of a specific gate policy |
codacy_cli (2)
Action | Description |
| Run local analysis via CLI |
| Install the CLI |
Setup
Requirements
Node.js โฅ 18
Configuration
Add to your MCP client configuration (Cursor, VS Code, Claude Desktop, etc.):
{
"mcpServers": {
"codacy": {
"command": "node",
"args": ["dist/server.js"],
"env": {
"CODACY_ACCOUNT_TOKEN": "<YOUR_TOKEN>"
}
}
}
}Development
npm install
npm run build # Compile TypeScript
npm run dev # Vurb dev server (hot-reload)
npm test # Run 105 tests
npm run inspect # MCP InspectorProject Structure
src/
โโโ agents/ # Tool definitions (Fluent API)
โ โโโ codacy_organizations.tool.ts
โ โโโ codacy_repositories.tool.ts
โ โโโ codacy_issues.tool.ts
โ โโโ codacy_security.tool.ts
โ โโโ codacy_tools.tool.ts
โ โโโ codacy_files.tool.ts
โ โโโ codacy_pull_requests.tool.ts
โ โโโ codacy_commits.tool.ts
โ โโโ codacy_overview.tool.ts
โ โโโ codacy_quality.tool.ts
โ โโโ codacy_cli.tool.ts
โโโ models/ # Zod schemas (data contracts)
โโโ views/ # Presenters (LLM-optimized output)
โโโ middleware/ # Auth, validation
โโโ prompts/ # MCP prompt templates
โโโ utils/ # Constants, rules, types
โโโ context.ts # API client + context factory
โโโ index.ts # Registry
โโโ server.ts # Entry pointUsage (MCP stdio)
This server runs as a stdio MCP transport โ the AI client launches it as a subprocess and communicates via stdin/stdout.
Cursor / Windsurf / Claude Desktop
Add to your MCP configuration file:
Cursor:
.cursor/mcp.jsonWindsurf:
.codeium/windsurf/mcp_config.jsonClaude Desktop:
claude_desktop_config.json
{
"mcpServers": {
"codacy": {
"command": "node",
"args": ["/absolute/path/to/codacy-vurb/dist/server.js"],
"env": {
"CODACY_ACCOUNT_TOKEN": "<YOUR_TOKEN>"
}
}
}
}VS Code (Copilot)
Add to your settings.json (Ctrl+Shift+P โ Preferences: Open User Settings (JSON)):
{
"mcp": {
"servers": {
"codacy": {
"command": "node",
"args": ["/absolute/path/to/codacy-vurb/dist/server.js"],
"env": {
"CODACY_ACCOUNT_TOKEN": "<YOUR_TOKEN>"
}
}
}
}
}Get your token
Generate an Account API Token
Paste it in the
CODACY_ACCOUNT_TOKENfield above
Build & run
npm install
npm run build
# The server starts automatically when the MCP client launches it via stdioLicense
Apache 2.0 โ see LICENSE.
Available Tools
5 toolscodacy_overviewARead-only
[INSTRUCTIONS] Returns category-level counts โ use these to identify which category has the most issues, then drill down with codacy_issues.list filtering by that category.
Get issue count breakdown by quality category (Security, Performance, CodeStyle, etc.).. Select operation via the action parameter. Actions: categories, issues
Workflow:
'categories': [INSTRUCTIONS] Returns category-level counts โ use these to identify which category has the most issues, then drill down with codacy_issues.list filtering by that category.
Get issue count breakdown by quality category (Security, Performance, CodeStyle, etc.).
'issues': [INSTRUCTIONS] Returns server-rendered ECharts pie charts. Do NOT try to recalculate or re-render โ present them as-is. Use the breakdown to identify highest-impact areas, then drill down with codacy_issues.list using appropriate filters.
Get aggregated issue overview with server-rendered pie charts by category and severity. [Cache-Control: no-store]
Inputs: action (required), provider, branchName, repository, +1 more.
codacy_pull_requestsBDestructive
[INSTRUCTIONS] Use ONLY when the user explicitly wants to override the quality gate โ this is a deliberate decision with security implications. Common mistakes: (1) Bypassing without user confirmation. (2) Bypassing for quality issues that could be fixed โ suggest fixing first. This action is idempotent โ calling it twice has no additional effect.
Bypass the analysis quality gate for a pull request. Allows merging even if quality standards are not met.. Select operation via the action parameter. Actions: bypass, get, list, coverage, diff, trigger_ai_review
Workflow:
'bypass': [INSTRUCTIONS] Use ONLY when the user explicitly wants to override the quality gate โ this is a deliberate decision with security implications. Common mistakes: (1) Bypassing without user confirmation. (2) Bypassing for quality issues that could be fixed โ suggest fixing first. This action is idempotent โ calling it twice has no additional effect.
Bypass the analysis quality gate for a pull request. Allows merging even if quality standards are not met.. Requires: pullRequestNumber [DESTRUCTIVE]
'get': [INSTRUCTIONS] isUpToStandards=false means the quality gate FAILED. Investigate with codacy_issues.pr_issues and codacy_pull_requests.coverage. Common mistake: treating isUpToStandards=null as passed โ null means analysis is not yet complete.
Get pull request details with quality analysis results (isUpToStandards, new/fixed issues, coverage).. Requires: pullRequestNumber
'list': [INSTRUCTIONS] Lists PRs with quality analysis status. Analysis reflects COMMITTED code only โ local changes are NOT visible. Common mistake: expecting analysis to update in real-time after a push โ there is processing delay. Use codacy_pull_requests.get to check if isAnalysed=true.
List pull requests in a repository with analysis status.
'coverage': Get file-level coverage data for the pull request diff.. Requires: pullRequestNumber
'diff': Get the Git diff for a pull request.. Requires: pullRequestNumber
'trigger_ai_review': [INSTRUCTIONS] This triggers NEW work โ use ONLY when the user explicitly asks for an AI code review. NOT idempotent โ each call dispatches a new review. Prerequisite: the PR must be analysed (isAnalysed=true). If not, suggest waiting for analysis to complete. Common mistake: triggering review on unanalysed PRs โ check with codacy_pull_requests.get first.
Trigger a Codacy AI-powered code review on a pull request.. Requires: pullRequestNumber [DESTRUCTIVE] [Cache-Control: no-store]
Inputs: action (required), limit, cursor, provider, +3 more.
codacy_qualityARead-only
[INSTRUCTIONS] Returns the full threshold configuration for a policy. Use the policyId from codacy_quality.list_policies. Thresholds define pass/fail conditions for issues, coverage, complexity, and duplication.
Get details of a specific gate policy including all thresholds.. Select operation via the action parameter. Actions: get_policy, get_settings, list_policies
Workflow:
'get_policy': [INSTRUCTIONS] Returns the full threshold configuration for a policy. Use the policyId from codacy_quality.list_policies. Thresholds define pass/fail conditions for issues, coverage, complexity, and duplication.
Get details of a specific gate policy including all thresholds.. Requires: policyId
'get_settings': [INSTRUCTIONS] Returns the quality gate configuration โ thresholds for issues, coverage, complexity, and duplication. These settings determine what isUpToStandards means for PRs and commits.
Get quality settings for a repository (commit/PR/repository thresholds).
'list_policies': [INSTRUCTIONS] Gate policies are organization-level quality rules applied to repositories. Common mistake: confusing policies with repository-specific settings โ policies are templates, settings are per-repo. isDefault=true means this policy applies to all repos without explicit overrides.
List gate policies for an organization. [Cache-Control: no-store]
Inputs: action (required), policyId, provider, repository, +1 more.
codacy_repositoriesADestructive
[INSTRUCTIONS] Returns the overall repository health: Grade (A-F scale), coverage %, complexity, issue count. Common mistake: assuming Grade=A means zero issues โ the grade is a composite score. Use codacy_issues.list for the actual issue breakdown.
Get repository details with analysis metrics (grade, coverage, complexity, issues).. Select operation via the action parameter. Actions: get, list_branches, setup
Workflow:
'get': [INSTRUCTIONS] Returns the overall repository health: Grade (A-F scale), coverage %, complexity, issue count. Common mistake: assuming Grade=A means zero issues โ the grade is a composite score. Use codacy_issues.list for the actual issue breakdown.
Get repository details with analysis metrics (grade, coverage, complexity, issues).
'list_branches': [INSTRUCTIONS] Lists all branches tracked by Codacy analysis. The default branch is the one being analyzed โ other branches may have limited or no analysis data.
List branches of a repository.
'setup': [INSTRUCTIONS] Use ONLY when the user explicitly wants to add a new repository for analysis. This is a multi-step action: it will (1) find the organization, (2) join it if needed, (3) find the repository, and (4) add or follow it. Common mistake: calling setup on an already-tracked repository โ it will return a success message without re-adding. This action invalidates organization and repository caches.
Add or follow a repository in Codacy. This sets up analysis tracking. [DESTRUCTIVE] [Cache-Control: no-store]
Inputs: action (required), provider, repository, organization.
codacy_securityADestructive
Get the security dashboard summary for a repository.. Select operation via the action parameter. Actions: dashboard, ignore, ossf_scorecard, sbom_search, search_org, search_repo
Workflow:
'dashboard': Get the security dashboard summary for a repository.
'ignore': [INSTRUCTIONS] Use when the user explicitly wants to mark a security finding as ignored. Always provide a reason: FalsePositive, WontFix, or NotRelevant. Common mistakes: (1) Do NOT invent reasons. (2) Ignoring without user confirmation โ this is a security decision, always confirm. This action is idempotent โ calling it twice with the same srmItemId has no additional effect.
Ignore or unignore a security finding.. Requires: srmItemId, reason [DESTRUCTIVE]
'ossf_scorecard': [INSTRUCTIONS] Accepts either a repository URL (e.g., https://github.com/org/repo) or a purl (e.g., maven:ch.qos.logback:logback-classic:1.2.3). At least one is required. Common mistake: not providing either url or purl โ the API requires at least one identifier. Use the purl from SBOM search results.
Get the OSSF Scorecard for a repository or package. Returns security posture score.
'sbom_search': [INSTRUCTIONS] Supply chain security investigation โ search SBOM dependencies by name, vulnerability severity, or risk category. Common mistakes: (1) Confusing SBOM search with security findings โ SBOM shows dependencies, use codacy_security.search_repo for code-level findings. (2) Risk categories: Forbidden, Risky, Normal โ do NOT invent categories. Use purl (Package URL) as the universal identifier for cross-referencing with OSSF Scorecard.
Search SBOM dependencies across the organization. Find vulnerable packages by name, severity, or risk category.
'search_org': [INSTRUCTIONS] Cross-repository security overview at the organization level. For repository-specific findings, use codacy_security.search_repo instead. Scan types: SAST, SCA, Secrets, IaC, CICD (repo-level). DAST and PenTesting are organization-level only. Common mistakes: (1) Using this for code quality issues โ use codacy_issues instead. (2) Status values: OnTrack, DueSoon, Overdue (open), ClosedOnTime, ClosedLate, Ignored (closed) โ do NOT invent statuses.
Search organization-level security findings across all repositories.
'search_repo': [INSTRUCTIONS] Repository-scoped security search. Uses the organization-level API filtered by this repository. Scan types available at repo level: SAST, SCA, Secrets, IaC, CICD. For DAST and PenTesting, use codacy_security.search_org instead. Common mistake: using DAST or PenTesting scan types here โ those are organization-level only.
Search security findings within a specific repository. [Cache-Control: no-store]
Inputs: action (required), url, purl, text, +14 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
TDQS
Scored across 5 tools
Each tool targets a distinct area: overview, pull requests, quality policies, repository metrics, and security. There is no functional overlap; agents can clearly differentiate them.
All tool names follow the pattern 'codacy_<noun>', using lowercase with underscores. The naming is uniform and predictable.
With 5 tools, the server covers the core aspects of code quality and security analysis without being excessive or insufficient. Each tool earns its place.
The tool set provides overviews, PR analysis, quality settings, repository metrics, and security. However, it lacks a dedicated tool for listing and managing individual code issues (the instructions reference a missing 'codacy_issues.list'), which is a notable gap for detailed investigation.
Maintenance
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