Agent Security MCP
Detects leaked GitHub personal access tokens (ghp_*, github_pat_*) and OAuth tokens.
Detects leaked JSON Web Tokens (JWT) in text or code.
Detects leaked MongoDB connection URIs (e.g., mongodb://).
Detects leaked MySQL connection URIs (e.g., mysql://).
Detects leaked OpenAI API keys (sk-*) in text or code.
Provides OWASP LLM Top 10 and Agentic Top 10 resources for security assessments.
Detects leaked PostgreSQL connection URIs (e.g., postgres://).
Detects leaked Redis connection URIs (e.g., redis://).
Detects leaked Slack tokens and webhooks.
Detects leaked Stripe live/test secret keys (sk_live_*, sk_test_*).
Detects leaked Telegram bot tokens.
Click on "Install 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., "@Agent Security MCPscan my MCP config for security issues"
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.
Agent Security MCP Server
Security scanning, prompt injection detection, secret leak detection, and agent permission auditing for AI agent workflows. Built on the Model Context Protocol (MCP).
Tools
Tool | Description |
| Scan MCP server configurations for security issues (dangerous commands, exposed secrets, network exposure, container misconfigs) |
| Analyze text for prompt injection attempts across 7 attack categories with context-aware risk scoring |
| Check if agent actions comply with scope contracts (tool allowlists, file access, boundary constraints) |
| Detect leaked API keys, tokens, private keys, database URIs, and credentials in text or code |
| Audit agent configurations against role-based expectations and flag principle of least privilege violations |
| Generate comprehensive security assessment reports with prioritized remediation plans |
| Analyze MCP tool definitions for hidden instructions that could manipulate agent behavior (OWASP Agentic Top 10) |
Related MCP server: ZugaShield
Resources
Resource | URI | Description |
OWASP LLM Top 10 |
| OWASP Top 10 for LLM Applications (2025) |
MCP Security Checklist |
| Security checklist for MCP server deployments |
Installation
cd agent-security-mcp
npm installUsage
As a standalone server
npm startIn Claude Desktop / MCP client configuration
{
"mcpServers": {
"agent-security": {
"command": "node",
"args": ["/path/to/agent-security-mcp/src/index.js"]
}
}
}With npx (after publishing)
{
"mcpServers": {
"agent-security": {
"command": "npx",
"args": ["@asl-throne/agent-security-mcp"]
}
}
}Detection Coverage
Prompt Injection (7 categories, 20+ patterns)
Instruction Override -- "ignore previous instructions", "disregard all rules", "new instructions:"
Identity Manipulation -- "you are now", "pretend you are", "act as", DAN/jailbreak
System Prompt Extraction -- "repeat your system prompt", "show your instructions"
Data Exfiltration -- "send this to", "post to webhook", "email everything to"
Delimiter Attacks -- ```system, [INST], <|im_start|>system, XML tag injection
Encoded Injection -- Base64 payloads, unicode zero-width characters, hex escapes
Privilege Escalation -- "sudo mode", "disable safety", "bypass filters"
Secret Detection (25+ patterns)
AI Provider Keys -- OpenAI (sk-), Anthropic (sk-ant-)
Cloud Credentials -- AWS (AKIA*), GCP (AIza*), Azure connection strings
Source Control -- GitHub PATs (ghp_*, github_pat_*), OAuth tokens (gho_*)
Payment -- Stripe live/test keys (sk_live_*, sk_test_*)
Communication -- Slack tokens/webhooks, Telegram bot tokens
Database -- PostgreSQL, MongoDB, MySQL, Redis connection URIs
Cryptographic -- RSA/EC/OpenSSH private keys, generic PEM blocks
JWT -- JSON Web Tokens
Generic -- api_key=, secret=, password=, .env file patterns
Permission Audit (6 role profiles)
Researcher -- Read + search + web only
Analyst -- Read + search only
Developer -- Read + write + execute
Reviewer -- Read only, no network
Orchestrator -- Read + write + task spawning
Monitor -- Read only, no network, no write
Pricing
Plan | Price | Servers | Features |
Free | $0 | 1 server | Single scan, basic report |
Starter | $49/month | 3 servers | Continuous scanning, weekly reports |
Pro | $199/month | 20 servers | Real-time alerts, CI/CD integration, Slack notifications |
Enterprise | $799/month | Unlimited | Custom policies, EU AI Act compliance reporting, SSO, dedicated support |
Requirements
Node.js >= 18.0.0
@modelcontextprotocol/sdk >= 1.12.0
License
MIT
Available Tools
8 toolsaudit_agent_permissionsB
Audit an agent configuration for over-privileged access. Compares granted permissions against role-based expectations (researcher, analyst, developer, reviewer, orchestrator, monitor). Flags principle of least privilege violations.
| Name | Required | Description | Default |
|---|---|---|---|
| role | Yes | The declared role of the agent (researcher, analyst, developer, reviewer, orchestrator, monitor) | |
| agent_config | Yes | Agent configuration to audit |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It does not mention whether the tool is read-only, modifies the agent configuration, requires permissions, or what the output format is (e.g., report structure). This lack of detail limits transparency.
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 at two sentences, with no unnecessary words. It is front-loaded with the action and purpose. However, some additional structure or bullet points could improve scanability, but overall it is efficient.
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 tool's complexity (nested object parameter, no output schema, no annotations), the description is incomplete. It does not explain what the output looks like (e.g., list of violations), whether it modifies state, or how to interpret flags. This leaves gaps for correct invocation.
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 for parameters is 100%, so the baseline is 3. The description does not add any extra meaning beyond what the schema already provides. It mentions 'role-based expectations' but does not specify how the role is used or clarify the nested 'agent_config' structure beyond the schema.
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 purpose: auditing an agent configuration for over-privileged access by comparing against role-based expectations. It uses a specific verb-resource pair ('audit agent configuration') and distinguishes itself from sibling security tools like 'scan_mcp_config' and 'detect_prompt_injection' which focus on different aspects.
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 implies usage for checking agent permissions but does not explicitly state when to use this tool versus alternatives. No exclusions or context about prerequisites are provided, making it adequate but not exemplary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detect_prompt_injectionA
Analyze text for prompt injection attempts. Detects instruction overrides, identity manipulation, system prompt extraction, data exfiltration, delimiter attacks, encoded injections, and privilege escalation. Context-aware risk scoring.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to analyze for prompt injection patterns | |
| context | Yes | Where this text originates — affects risk scoring (user_input is highest risk) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral burden. It mentions 'context-aware risk scoring' and lists detected patterns, but does not disclose what happens after detection (e.g., returns a boolean, score, or flagged text). No side effects or safety info is given.
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?
Two sentences, no wasted words. First sentence states the core purpose, second adds meaningful detail. Well front-loaded.
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?
Input parameters are well covered, but no output schema exists and the description omits any mention of return values or structure. For a detection tool, understanding the output format is important for correct usage.
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 schema covers 100% of parameters with descriptions. The description adds 'context-aware risk scoring' and lists specific injection types, providing meaning beyond the raw parameter definitions, especially for the 'context' enum values.
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 'Analyze text for prompt injection attempts' and lists specific attack types (instruction overrides, identity manipulation, etc.), which is a specific verb+resource. Among sibling security tools, it uniquely targets prompt injection, so it distinguishes well.
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 versus alternatives like scan_secrets or detect_tool_poisoning. It implies usage for analyzing text for injection, but provides no exclusion criteria or context-based guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detect_tool_poisoningA
Analyze an MCP tool definition for poisoning indicators — hidden instructions in descriptions that could manipulate agent behavior. Covers OWASP Agentic Top 10 tool poisoning attack vectors.
| Name | Required | Description | Default |
|---|---|---|---|
| tool_definition | Yes | The MCP tool definition to analyze |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should fully disclose behavior. It mentions the analysis scope (OWASP vectors) but does not state that the tool is read-only, safe, or non-destructive. It also lacks details on potential side effects or rate limits.
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 two sentences, concise and front-loaded with the core purpose. Every sentence is meaningful, and there is no redundant information.
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 lacks any mention of the return value or output format, which is critical for a security analysis tool. Users and AI agents need to know what the result looks like (e.g., risk score, list of indicators). Additionally, no output schema is provided, and annotations are absent.
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 single parameter 'tool_definition' is fully described in the schema (100% coverage), but the description adds value by explaining that the tool analyzes the description text for hidden instructions and covers specific attack vectors, going beyond the schema's generic description.
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 analyzes MCP tool definitions for poisoning indicators, specifically hidden instructions in descriptions that manipulate agent behavior, covering OWASP Agentic Top 10 attack vectors. It is specific and distinguishes from siblings like detect_prompt_injection.
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 implies usage when analyzing tool definitions for poisoning, but it does not provide explicit guidance on when to use this tool versus alternatives like detect_prompt_injection or validate_scope_contract. No when-not-to-use or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_security_reportA
Generate a comprehensive security assessment report for an agent deployment. Aggregates results from config scans and permission audits into a prioritized remediation plan with OWASP LLM Top 10 compliance notes.
| Name | Required | Description | Default |
|---|---|---|---|
| configs | No | Array of scan_mcp_config results to include in the report | |
| agent_name | Yes | Name of the agent or deployment being assessed | |
| audit_results | No | Array of audit_agent_permissions results to include in the report |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that the tool aggregates inputs and produces a report with a remediation plan and compliance notes. It does not explicitly state that it is read-only or non-destructive, but the nature of generating a report implies no side effects. Lacks explicit safety statements like 'does not modify any state.'
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?
Two concise sentences with no wasted words. The key action and output are front-loaded: 'Generate a comprehensive security assessment report.' Every sentence adds distinct value.
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 no output schema, the description adequately explains the output (remediation plan with OWASP notes). It does not detail the output structure or format, but the mention of aggregation and prioritization provides sufficient context. Parameter coverage is complete.
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%, so the schema already describes each parameter. The description adds value by explaining that configs come from scan_mcp_config and audit_results from audit_agent_permissions, clarifying their provenance. However, it does not provide format or constraints beyond what the schema offers.
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 verb ('Generate'), the resource ('comprehensive security assessment report'), and the scope ('for an agent deployment'). It explicitly mentions aggregating results from config scans and permission audits and producing a prioritized remediation plan with OWASP compliance notes. This distinguishes it from sibling tools like scan_mcp_config and audit_agent_permissions, which are single-purpose scanners.
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 implies usage after running config scans and permission audits (since it aggregates their results), but does not explicitly state prerequisites or when not to use it. Alternatives are implied by sibling tools (e.g., use scan_mcp_config for scans instead), but no direct guidance on exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
health_checkA
Returns server health, uptime, version, and usage stats
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses it returns metrics (read-only), but does not mention authorization needs, rate limits, or potential side effects. For a simple health check, this is adequate but minimal.
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?
Single sentence, no filler, front-loaded with the verb. Every word earns its place.
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 zero-parameter health check tool, the description is sufficient to convey purpose and output. However, without an output schema, an agent might benefit from hinting at the structure (e.g., 'returns JSON object'). Still, given simplicity, a 4 is appropriate.
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?
With zero parameters and 100% schema coverage, the description adds no additional meaning for parameters, which is acceptable. The baseline is 4 since no parameter documentation is needed.
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?
Description clearly states the action ('returns') and specific resources ('server health, uptime, version, and usage stats'), making the purpose unambiguous. It also distinguishes from sibling security-focused tools like scan_mcp_config or detect_prompt_injection.
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 implies usage for server monitoring but provides no explicit guidance on when to use this tool versus alternatives. Given siblings are all security-related, the distinction is clear, but no when-not or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_mcp_configA
Scan an MCP server configuration for security issues including dangerous commands, exposed secrets, network exposure, and container misconfigurations. Returns a risk score (0-100), issues found, and actionable recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| config | Yes | MCP server configuration object | |
| server_name | Yes | Name of the MCP server being scanned |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It explains the scanning scope and return values (risk score, issues, recommendations), which is helpful. However, it does not state whether the tool modifies state, requires authentication, or is read-only. The absence of such details limits transparency.
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?
Two concise sentences: first states purpose and what it scans for, second states outputs. No fluff, front-loaded with key actions and results. Every sentence adds value.
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 no output schema, the description outlines return values (risk score, issues, recommendations). The tool fits well among sibling security tools. It covers scope and output adequately but could mention idempotency or permissions. Still, it provides sufficient context for an agent to decide 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?
Schema description coverage is 100% (both parameters documented in schema). The description adds no new meaning beyond 'scan an MCP server configuration' — the schema already defines config object with command, args, env, and server_name. Baseline 3 applies as the description does not enhance parameter understanding.
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 uses a specific verb 'Scan' and resource 'MCP server configuration', listing concrete security issue categories (dangerous commands, exposed secrets, network exposure, container misconfigurations) and outputs (risk score, issues, recommendations). It clearly distinguishes from sibling tools like 'scan_secrets' or 'detect_prompt_injection'.
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?
No explicit guidance on when to use this tool versus alternatives (e.g., scan_secrets, detect_prompt_injection). The description does not mention prerequisites, when to avoid, or when other tools are more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_secretsA
Detect leaked secrets and credentials in text or code. Identifies API keys (OpenAI, AWS, GitHub, GCP, Stripe, Slack, Telegram), JWT tokens, database connection strings, private keys, and .env patterns. All values are masked in output.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | The text or code content to scan for secrets | |
| content_type | Yes | Type of content being scanned — affects detection sensitivity |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: 'All values are masked in output.' However, it does not mention whether the tool is read-only, if it has rate limits, or any permission requirements.
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?
Two sentences: first states purpose, second provides key detail about output masking. No wasted words, front-loaded with the action.
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?
No output schema exists, so the description should explain the return format. It only says 'All values are masked in output,' which is vague. Missing details on result structure and error cases, but sufficient for a simple detection 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% and the description does not add significant new meaning beyond what the schema already provides. The description lists secret types, which provides context, but does not elaborate on parameter formats or constraints.
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?
Description starts with a clear verb-resource pair: 'Detect leaked secrets and credentials in text or code.' It lists specific secret types (API keys, JWT tokens, etc.), which distinguishes it from sibling tools like health_check or detect_prompt_injection.
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?
No explicit guidance on when to use this tool versus alternatives. The description implies it's for scanning text/code for secrets, but does not mention prerequisites, when not to use, or suggest sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_scope_contractA
Check if an agent action complies with its scope contract. Validates tool usage against allowlists, file access against permitted paths, and boundary constraints (no_network, read_only, no_exec, no_secrets).
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | The action to validate against the scope contract | |
| scope_contract | Yes | The agent scope contract defining permitted actions |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full transparency burden. It describes what is validated but omits critical behavioral details: whether it is read-only, what happens on violation (return value, error, side effects), and performance implications. This is insufficient for an agent to predict outcomes.
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?
Two sentences efficiently convey purpose and scope. Every word adds value, no redundancy or filler. Well-structured for quick parsing.
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 nested objects and validation complexity, the description covers the 'what' but not the 'how' (output format, error handling). Missing output schema means agents need to guess return structure. Adequate but not fully complete.
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 descriptions for both parameters. The tool description adds overall context but no new parameter details. Baseline 3 is appropriate as schema already documents parameters.
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 verifies compliance of an agent action with its scope contract, listing specific checks (tool allowlists, file paths, boundary constraints). This distinguishes it from sibling tools like health_check or scan_mcp_config which focus on different security aspects.
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 implies usage for validation but does not explicitly state when or when not to use it. It contrasts with siblings only implicitly through purpose. No guidance on prerequisites or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
8 tool updates
v0.1.3- First observed
audit_agent_permissions - First observed
detect_prompt_injection - First observed
detect_tool_poisoning - First observed
generate_security_report - First observed
health_check - First observed
scan_mcp_config - First observed
scan_secrets - First observed
validate_scope_contract
TDQS
Each tool addresses a distinct security concern: health, config scanning, prompt injection, scope validation, secrets, permissions, reporting, and tool poisoning. No functional overlap.
All tool names follow a consistent verb_noun pattern (e.g., scan_mcp_config, detect_prompt_injection), making the set predictable and easy to navigate.
8 tools cover a comprehensive range of security operations without being excessive; each tool earns its place for the server's stated purpose.
The tool set covers all major security assessment areas for MCP agents: scanning, detection, validation, auditing, and reporting, leaving no obvious gaps.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Security gateway for AI agents: policy, approval, and audited execution, no secrets shared.
The WAF for agents. Pattern-based + heuristic firewall scans prompts, RAG documents, tool argume...
Deterministic runtime safety for AI agents: scan PII, gate tool actions, verify LLM output.
Pay-per-call cybersecurity for AI agents: vuln scans, threat intel, compliance, code security.
Related MCP Servers
- AlicenseAqualityBmaintenanceProtects AI agents from threats like prompt injection, jailbreaks, and SQL injection through a multi-layer scanning pipeline. It also enables PII redaction and rehydration to ensure data privacy during LLM interactions.121252Apache 2.0
- AlicenseNot gradedqualityAmaintenanceA 7-layer security system for AI agents that detects and blocks prompt injection, data exfiltration, and malicious tool calls. It enables real-time scanning of inputs, outputs, and tool definitions to protect agentic workflows from emerging AI-specific threats.1MIT
- AlicenseAqualityCmaintenanceSecurity co-pilot for AI agents. Scans for vulnerabilities like prompt injection, infinite loops, and token bombing in AI Agents, audits MCP servers, verifies AGENTS.md governance, and generates EU AI Act compliance reports.10863Apache 2.0
- AlicenseAqualityDmaintenanceOpen-source permission control plane for AI agents — scan, enforce, and audit every tool call with code-level policies that prompt injection can't bypass.1419Business Source 1.1
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/mdfifty50-boop/agent-security-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server